Campbell et al v. Facebook Inc.
Filing
137
Administrative Motion to File Under Seal re Plaintiffs' Motion for Class Certification filed by Matthew Campbell, Michael Hurley. (Attachments: # 1 Proposed Order, # 2 Certificate/Proof of Service, # 3 Declaration of Melissa Gardner, # 4 Exhibit A, # 5 Exhibit B, # 6 Exhibit C, # 7 Exhibit D, # 8 Exhibit E, # 9 Exhibit F, # 10 Exhibit G, # 11 Exhibit H, # 12 Exhibit I, # 13 Exhibit J, # 14 Exhibit K, # 15 Exhibit L, # 16 Exhibit M, # 17 Exhibit N, # 18 Exhibit O, # 19 Exhibit P, # 20 Exhibit Q, # 21 Exhibit R, # 22 Exhibit S, # 23 Exhibit T, # 24 Exhibit U, # 25 Exhibit V, # 26 Exhibit W, # 27 Exhibit X, # 28 Exhibit Y, # 29 Exhibit Z, # 30 Exhibit AA, # 31 Exhibit BB, # 32 Exhibit CC, # 33 Exhibit DD)(Gardner, Melissa) (Filed on 11/13/2015)
EXHIBIT D
REDACTED VERSION OF
DOCUMENT(S) SOUGHT TO BE SEALED
EXHIBIT 2
REDACTED VERSION OF DOCUMENT(S) SOUGHT TO BE SEALED
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Michael W. Sobol (State Bar No. 194857)
msobol@lchb.com
David T. Rudolph (State Bar No. 233457)
drudolph@lchb.com
Melissa Gardner (State Bar No. 289096)
mgardner@lchb.com
LIEFF CABRASER HEIMANN & BERNSTEIN, LLP
275 Battery Street, 29th Floor
San Francisco, CA 94111-3339
Telephone: 415.956.1000
Facsimile: 415.956.1008
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Hank Bates (State Bar No. 167688)
hbates@cbplaw.com
Allen Carney
acarney@cbplaw.com
David Slade
dslade@cbplaw.com
CARNEY BATES & PULLIAM, PLLC
11311 Arcade Drive
Little Rock, AR 72212
Telephone: 501.312.8500
Facsimile: 501.312.8505
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Attorneys for Plaintiffs and the Proposed Class
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UNITED STATES DISTRICT COURT
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NORTHERN DISTRICT OF CALIFORNIA
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MATTHEW CAMPBELL and MICHAEL
HURLEY, on behalf of themselves and all
others similarly situated,
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Plaintiffs,
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v.
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FACEBOOK, INC.,
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Defendant.
Case No. C 13-05996 PJH (MEJ)
REPORT OF DR. JENNIFER GOLBECK
IN SUPPORT OF PLAINTIFFS’ MOTION
FOR CLASS CERTIFICATION
HEARING
Date: March 16, 2016
Time: 9:00 a.m.
Place: Courtroom 3, 3rd Floor
|
The Honorable Phyllis J. Hamilton
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REPORT OF DR. GOLBECK IN SUPPORT OF
PLAINTIFFS’ MOTION FOR CLASS CERTIFICATION
C 13-05996 PJH (MEJ)
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TABLE OF CONTENTS
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Page
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I.
II.
III.
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IV.
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V.
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VI.
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VII.
VIII.
IX.
QUALIFICATIONS ............................................................................................... 1
METHODOLOGY AND SUMMARY OF CONCLUSIONS ............................... 3
FACEBOOK’S INTERCEPTION OF PRIVATE MESSAGE CONTENT........... 5
A.
Facebook’s Private Message Architecture Functionality............................ 5
B.
Facebook’s Interception and
of Private Message Content ........... 9
C.
Facebook’s Use Of Code-Based Devices To Intercept Private
Message Content ....................................................................................... 14
FACEBOOK’S USES OF INTERCEPTED PRIVATE MESSAGE DATA ....... 15
A.
Facebook Used Private Message Content To
And Other Features ............. 15
B.
Incrementing Like Counter ....................................................................... 23
FACEBOOK’S CONDUCT
........................ 26
A.
Facebook Has
........................................... 26
CLASS MEMBERS ARE ASCERTAINABLE ................................................... 27
A.
Class Members Can Be Identified Through
. ................ 27
THE CODE FOR ANALYZING PRIVATE MESSAGES OPERATED
THE SAME FOR ALL USERS ............................................................................ 29
“ORDINARY COURSE OF BUSINESS” .......................................................... 29
“IN TRANSMISSION” ........................................................................................ 32
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I.
QUALIFICATIONS
1.
As indicated in my curriculum vitae, attached hereto as Exhibit A, I have been a
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professor in the College of Information Studies (“The iSchool”) at the University of Maryland
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since 2007 (assistant professor from 2007-2013, associate professor with tenure to present),
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where I have focused my research and teaching efforts on aspects of social media and the web.
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2.
I have been doing freelance professional web design and programming since 1993.
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I worked as a web designer for the University of Chicago from 1995-2000. I operated my own
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web design company, Gargoyle Web Design, from 1999-2001, which I closed when I began my
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Ph.D. work.
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3.
I have taught university level classes on the web and social media, including:
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“Analyzing Social Networks and Social Media,” “Social Networks: Technology and Society,”
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“Development of Internet Applications,” “Fundamentals of Human-Computer Interaction,”
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“Information Users in Social Context,” and “Small Worlds, Social Networks, and Algorithms.” In
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addition, I have published and presented many articles in refereed journals and conferences, and
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over 100 of these relate to social media and the web.
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4.
I received two Bachelor’s degrees, in Computer Science and Economics, from the
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University of Chicago in 1999, a Master’s degree in Computer Science from the University of
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Chicago in 2001, and a Ph.D. in Computer Science from the University of Maryland in 2005. My
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Ph.D. thesis focused on social media and was titled “Computing and Applying Trust in Web-
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based Social Networks.”
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5.
I have been teaching at universities on issues related to computer science, the web,
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and social media since 1999 when I was a Lecturer in the Computer Science Department at the
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University of Chicago. Over the past fourteen years, in a variety of different capacities, I have
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taught classes at University of Chicago, George Mason University, Johns Hopkins University,
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Georgetown University, George Washington University, American University, and University of
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Maryland.
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6.
Through my research and studies, I have won a variety of awards including the
2015 University of Maryland Research Communicator Impact Award, 2015 University of
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REPORT OF DR. GOLBECK IN SUPPORT OF
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Maryland System Mentoring Award, Best Paper Award at the 2011 IEEE Social Computing
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Conference, Best Paper Award at the 2009 International Semantic Web Conference, Research
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Fellow for the Web Science Research Initiative (2008 – present), IEEE Intelligent Systems Ten to
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Watch in May 2006, and the 2005 DARPA IPTO Young Investigator Award.
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7.
I also presented a TED talk titled “The curly fry conundrum: Why social media
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‘likes’ say more than you might think.”1 It received 1.7 million views and was named one of
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TED’s “Most Powerful Talks of 2014.”2 TED (Technology, Engineering, Design) is a non-profit
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organization that presents “Ideas Worth Spreading.” Videos of their invited presentations have
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over half a billion total views.
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8.
I have authored over 100 scientific papers related to the web. Most recently, I have
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authored two books on social media, entitled “Social Media Investigation” and “Analyzing the
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Social Web.” Both books focus on various aspects of web and social media interaction, such as
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using location-based services on mobile devices as well as interaction with friends for business
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purposes. I have also authored other books including “Trust on the World Wide Web: A Survey”
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and “Art Theory for Web Design.”
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9.
I have given expert testimony in the following proceedings:
•
Rembrandt Social Media LP v. Facebook Inc. et al, No. 13-cv-00158
U.S. District Court for the Eastern District of Virginia
2013-2014 (plaintiff)
•
Peter Daou and James Boyce vs. Ariana Huffington, Kenneth Lerer and
Thehuffingtonpost.com, No. 651997/2010
Supreme Court of The State Of New York, County of New York 20132014 (plaintiff)
•
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Blue Calypso Inc. v. Groupon Inc., No. 12-cv-00486,
U.S. District Court for the Eastern District of Texas
2014-2015 (plaintiff)
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Available at
https://www.ted.com/talks/jennifer_golbeck_the_curly_fry_conundrum_why_social_media_likes
_say_more_than_you_might_think?language=en.
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See http://yearinideas.ted.com/2014/.
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10.
A copy of my full curriculum vitae is attached as Exhibit A to this report. I am
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being compensated at the rate of $400 per hour for my services in this matter, and payment is not
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contingent on the outcome of this proceeding.
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II.
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METHODOLOGY AND SUMMARY OF CONCLUSIONS
11.
I am submitting this report on behalf of the Plaintiffs. I have been retained as a
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technical expert to study and provide my opinions regarding the topics discussed in paragraph 16
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below. My opinions, as well as the evidence I rely upon to support them, are set forth in detail in
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this report. The contents of the various exhibits that I identify by name are meant to be
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incorporated, in their entirety, by such reference.
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12.
In preparing this report, I have employed methods and analyses of a type
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reasonably relied upon by experts in my field in forming opinions or inferences on the subject.
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The opinions expressed are based upon a reasonable degree of computer science certainty.
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13.
Between now and such time that I may be asked to testify before the Court, I
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expect to continue my review, evaluation, and analysis of information generated during
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discovery, as well as of relevant evidence presented before and/or at trial. I also expect to review
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the reports submitted by Facebook’s experts. I reserve the right to amend or supplement this
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report, as necessary and as acceptable to the Court. I also reserve the right to develop materials
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and exhibits as appropriate for use in helping to demonstrate and explain my opinions in the event
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that I am asked to testify at trial.
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14.
In forming my opinions, I have reviewed source code which I understand was
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provided by Facebook’s counsel and which was represented as containing the relevant source
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code between some time in 2009 and December 2012.
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15.
Additionally I have reviewed numerous internal Facebook documents produced in
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this litigation, as well as certain public materials. The list of documents I have considered in
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forming my opinions is attached to this report as Exhibit B.
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16.
I have been asked by the Plaintiffs through their counsel to opine on the following
issues:
a.
The structure and function of Facebook’s messaging system;
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b.
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Facebook’s interception of Private Message content, including:
i.
Whether and what devices Facebook employs to intercept message
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ii.
Whether the interceptions occurred in transit;
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iii.
Whether the interception of Private Message content was necessary
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content;
for Facebook to deliver private messages;
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c.
Facebook’s subsequent use of that Private Message content;
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d.
Whether the class members can be readily determined based on Facebook’s
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own records; and
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e.
Whether the Facebook’s uniformly processed Private Messages during the
relevant period.
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Based on my review and analysis of Facebook’s source code as well as internal
Facebook documents and deposition testimony, I conclude the following:
a.
The structure and function of Facebook’s messaging system is described in
detail in Section III below;
b.
Facebook intercepted and redirected user’s Private Message content using
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various code-based devices while the message was in transit, and this interception was not
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necessary for Facebook to deliver private messages;
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c.
Facebook used the intercepted Private Message content
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as well as to increment the “Like” social plugin counter;
d.
The class members can be determined from Facebook’s own records using
various query methods and through self-identification; and
e.
Facebook’s source code operated consistently during the relevant period.
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III.
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FACEBOOK’S INTERCEPTION OF PRIVATE MESSAGE CONTENT
A.
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Facebook’s Private Message Architecture Functionality
1.
18.
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Overview of Facebook’s Private Message Architecture
An overview of Facebook’s Private Message architecture is useful. Say Alice is
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sending a Private Message to Bob. In order to do so, Alice opens her Facebook message window
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and begins to compose her message.
Figure 1
Message Window
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She types her text and, if she types, pastes, or otherwise enters a URL into the
body of the message,
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20.
Facebook describes this process in its Supplemental Responses and Objections to
Plaintiffs’ First Set of Interrogatories:
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Facebook’s servers are the computers on which the Facebook system operates. They store code
and data, run the code, provide web content, and manage back-end functionality. Essentially,
every part of Facebook other than the code that runs in the user’s browser is running on Facebook
servers, and those servers provide every element of Facebook that a user interacts with.
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21.
The vast majority of web users have JavaScript enabled. In 2010, Yahoo!
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engineers issued a report stating that 1-2% of traffic came from users without Javascript enabled.5
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Those numbers appear to have remained relatively stable over time. A 2013 analysis showed
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about 1% of users were not accessing JavaScript-based content.6 Thus, 98-99% of users have
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JavaScript active and this Facebook code would run in their browsers.
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22.
The URL detection process is also described by Ray He, an engineer at Facebook.
In his September 25, 2015 deposition (He Depo.), Mr. He states:
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Based on my analysis of Facebook’s source code (the “Code”), this process
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appears in
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Id. at 12:26 – 13:2.
See
https://web.archive.org/web/20101016010319/http://developer.yahoo.com/blogs/ydn/posts/2010/
10/how-many-users-have-javascript-disabled/
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See https://gds.blog.gov.uk/2013/10/21/how-many-people-are-missing-out-on-javascriptenhancement/
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He Depo. at 187:7-11.
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FB000027054; FB000027055.
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24.
After this Code
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The process of
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As mentioned above,
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The preview then appears as part of the message that the Alice is composing
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Facebook’s Supplemental Responses and Objections to Plaintiffs’ First Set of Interrogatories at
13:4-5.
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The
is analogous to the “web crawler” referenced in Plaintiffs’ Consolidated
Amended Complaint (“CAC”).
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API stands for “Application Program Interface.” It's a set of code one can use to interact with a
system (Facebook in this case).
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FB000027055
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Facebook’s Supplemental Responses and Objections to Plaintiffs’ First Set of Interrogatories at
13:19-20
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Figure 2
Message Window
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However, this preview in Alice’s message is not the
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. The preview returned is
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As described in further detail below,
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prior to Alice’s typing
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the URL into her Private Message, Facebook’s
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.
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30.
When Alice finishes the message and hits send, both the text of her message and
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the
are sent to Facebook’s servers. In a series of steps, detailed further below,
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Facebook processes the message
, ultimately delivering the message to Bob. For
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that high level message sending to happen, there are many sub-processes that have to take place.
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Facebook’s Supplemental Responses and Objections to Plaintiffs’ First Set of Interrogatories at
14:5.
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Michael Adkins, a Facebook engineer, provides a broad overview of this transmission process in
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his October 28, 2015 deposition (Adkins Depo.):
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31.
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The focus of this report, which is the interception and acquisition of the
in Private Messages, occurs early in the above-described transmission,
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.
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B.
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Facebook’s Interception and
1.
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32.
of Private Message Content
Creation of Share Objects
Facebook has large and complex data behind its site. They store this in a data
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model called TAO (The Associations and Objects).16 As the name suggests, there are two pieces
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in this model: objects and associations.
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33.
Objects represent things on Facebook – users, pages, checkins, comments,
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locations, etc. Associations represent relationships between objects. Those could be friendships
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between users, a like that connects a user to a page, or a location that is tied to a user check-in.
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34.
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There are a number of objects that Facebook
. Two of these are
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objects and
Adkins Depo. at 67:23-69:1. Similarly, Ray He stated in his deposition that
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He Depo. at 204:21-24
See https://www.facebook.com/notes/facebook-engineering/tao-the-power-of-thegraph/10151525983993920
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objects. The
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, while the
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.
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35.
As described in the previous section, when Facebook is generating the preview for
a URL in a user’s message window,
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It is
information from this
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object that is used to
. If no
object exists, Facebook’s
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36.
Based on my analysis of Facebook’s Code, this is the process for the
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Facebook’s Supplemental Responses and Objections to Plaintiffs’ First Set of Interrogatories at
13:8-11
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cific
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39.
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Facebook or not,
When the user sends a Private Message containing a URL, whether it is new to
incremented. In other words,
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goes up by 1. The process for this
is as follows.
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40.
After the user hits “send” but before the message is delivered, the Facebook Code
processes information about the sent message. Specific to this litigation, the Code searches for
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.
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These
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internal documentation, “
According to Facebook’s
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In the case of
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FB000014199.
In some cases, this includes a
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FB000014204.
FB000011543.
the private message as the
, known in this case as
. See
Facebook’s Second Supplemental Responses and Objections to Plaintiffs’ Narrowed Second Set
of Interrogatories at14:5-6:
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Private Messages,
while composing a private message.22
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3
41.
The creation of the
in
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the message transmission process. As discussed in greater detail in Section III.B, infra, the Code
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in
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42.
Based on my analysis of Facebook’s Code and documents, in my opinion, and as
discussed further below, the
10
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constitute the
interception, analysis, and use of the contents of user’s Private Message.
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2.
13
43.
of Private Message Content
Once Facebook intercepts the URL contents of users’ Private
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a.
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44.
Facebook’s Code, as well as Facebook’s internal documents, indicate that when a
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.
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45.
The
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With this data, Facebook can
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in a variety of ways. The URLs people share privately may
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46.
For example, on
Private Message content.23
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An example of the data represented in
is FB000005528.
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The particular Facebook functionality at issue in this document is
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documents describe as
which Facebook
”24 Ray He further explains that
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47.
Concerning
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This
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indicates if a message was
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This is further corroborated by a
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Messages were
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48.
This could only be the case if Private
.
Indeed,
in
a later communication, dated
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49.
In the Facebook Code base, the
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50.
Again, the presence of the
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.
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FB000002651.
FB000003118.
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He Depo. at 227:3-4, 11-12.
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FB000002651.
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FB000002843.
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FB000014183.
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51.
2
3
6
is now used to
, Facebook could still use information from the Private Messages in the future
since they
4
5
While the addition of the
.
b.
52.
. In Facebook document
FB000008505, Facebook employees describe the
7
8
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53.
In the same document describing this
54.
When a URL is
C.
Facebook’s Use Of Code-Based Devices To Intercept Private Message
Content
55.
As discussed above, Facebook employs various code-based devices to intercept
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Private Message content. Set forth below are the discrete components of Facebook’s Code that
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execute the interceptions, each of which
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• Processes
:
o After a user sends a message, the Code
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o As described in section III.B.2 above,
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•
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o As described more detail in in paragraph 84 below,
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.
IV.
FACEBOOK’S USES OF INTERCEPTED PRIVATE MESSAGE DATA
A.
Facebook Used Private Message Content To
And Other Features
56.
With the data Facebook collected by scanning Private Messages, Facebook
14
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18
.
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1.
Facebook Provided
20
57.
As described above, the
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58.
The Code for
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this is as follows:
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59.
In this
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60.
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10
2.
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61.
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. This, along with other evidence, strongly
suggests that Facebook continued to use Private Message content to
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62.
As discussed above,
63.
In deposition, Ray He explained that
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FB000027029.
FB000027051.
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64.
Mr. He provided further testimony confirming that Private Message URL sends
were used in
. When discussing how
6
, Ray He was asked whether he was
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”32
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3.
13
65.
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. This includes interactions that took place in private messages.
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66.
In FB000007286, Facebook describes
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31
32
He Depo. at 234:14-25.
He Depo. at 229:19-230:6.
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Figure 3
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67.
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18
68.
Facebook document FB000006178, which has the subject
69.
Section 4.2 of Facebook document FB000010688 describes
19
20
21
22
23
24
25
26
27
28
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Figure 4
2
3
4
5
6
7
8
The document goes on to explain that the
9
10
70.
As described above,
71.
This indicates that
72.
Facebook document FB000008722 also supports this. It describes
73.
In the
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
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74.
Experiments by journalist Ashkan Soltani also suggest that Facebook was
2
3
4
5
Figure 5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
4.
23
75.
24
25
The Facebook Activity Plugin allowed third parties to show recent activity in
Facebook that related to their site: 33
26
27
28
33
https://web.archive.org/web/20101205130048/http://developers.facebook.com/
docs/reference/plugins/activity.
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The Activity Feed plugin displays the most interesting recent
activity taking place on your site. Since the content is hosted by
Facebook, the plugin can display personalized content whether or
not the user has logged into your site. The activity feed displays
stories both when users like content on your site and when users
share content from your site back to Facebook. If a user is logged
into Facebook, the plugin will be personalized to highlight content
from their friends. If the user is logged out, the activity feed will
show recommendations from your site, and give the user the option
to log in to Facebook.
2
3
4
5
6
The plugin is filled with activity from the user’s friends. If there
isn’t enough friend activity to fill the plugin, it is backfilled with
recommendations. If you set the recommendations param to true,
the plugin is split in half, showing friends activity in the top half,
and recommendations in the bottom half. If there is not enough
friends activity to fill half of the plugin, it will include more
recommendations.
7
8
9
10
76.
11
12
13
14
15
16
17
77.
18
19
20
21
22
23
24
25
26
27
28
34
35
FB000002843.
Id.
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78.
2
3
4
5
5.
79.
Private Message data
80.
Facebook document FB000008499 describes the data that can be seen from
6
7
8
9
10
11
12
13
14
15
16
:
17
Figure 6
18
19
20
21
22
23
81.
24
25
26
27
28
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B.
Incrementing Like Counter
2
82.
On October 3, 2012, the Wall Street Journal reported that Facebook was scanning
3
users’ private messages.36 They detected this by observing that the like count on an external page
4
would increase by two every time the page’s URL was sent in a private message.
83.
5
They tested this by creating pages and observing the count on the external like
6
button increase by two every time the link was sent in a private message. The double counting
7
was also visible on the insights page for webmasters, which shows analytics information.
37
84.
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
36
37
http://blogs.wsj.com/digits/2012/10/03/how-private-are-your-private-messages/.
https://developers.facebook.com/blog/post/476.
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
85.
After media reports surfaced the double-counting issue and the fact that private
messages were scanned and hidden “likes” were counted as a result, Facebook
16
17
18
19
20
21
86.
In Facebook document FB000002141, Facebook discusses
22
23
24
25
26
27
28
38
FB000027018.
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2
3
87.
Facebook then set out to determine
4
5
.40
6
7
88.
Because the magnitude of
8
9
10
11
12
13
which messages are sent or
received.
14
89.
Indeed, the described change to the Code simply
90.
Changes in
15
16
17
18
19
do not impact the way that
Facebook handles private messages in any way. The Code change that
20
21
22
23
24
91.
This is further highlighted in Facebook document FB000006429. That document,
which discusses
25
26
27
28
39
40
FB000002196.
FB000001599.
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2
3
92.
Note that in the changes discussed above, Facebook
93.
This is supported in an email from
4
5
6
7
8
9
10
11
12
41
13
14
V.
15
FACEBOOK’S CONDUCT CONTINUES TO THE PRESENT
A.
Facebook Has
94.
In addressing the issue of
16
17
18
This appears redacted in FB000001606. However, there is no evidence
19
that Facebook ever
.
20
95.
Instead, evidence from the Code shows that Facebook
21
(the last date
22
for which we had access to source Code). I analyzed the files
23
24
25
. There were no substantial changes to these files, and they
26
continued to
until the latest date in the Code.
27
28
41
FB000000425.
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96.
Further, internal Facebook documents indicate that Facebook
2
3
4
My
understanding is that Facebook produced several
5
6
7
for the message’s URL.43
8
9
97.
With that information available, Facebook could
10
11
12
VI.
CLASS MEMBERS ARE ASCERTAINABLE
13
A.
Class Members Can Be Identified Through
14
98.
Each
99.
In the Code, the
.
15
16
17
18
19
20
21
22
23
44
24
25
26
27
28
42
FB000005827.
FB000005802-R.
44
FB0000027020.
43
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100.
The creator of these private
2
3
as shown below in FB000008499:
Figure 7
4
5
6
7
8
9
10
11
101.
This
12
. That resolves to
13
14
15
16
17
18
102.
person Facebook users located within the United States who have sent, or received from a
Facebook user, private messages that included URLs in their content (and from which Facebook
generated a URL attachment), from within two years of the filing of this action up through the
date of class certification.”
19
20
I understand that the Plaintiffs in this case seek to certify a class of “All natural-
103.
To retrieve a list of class members, the Code process should be relatively
straightforward. A database query could be used
21
22
23
104.
The exact code will vary based on the type of database, but example query code
could roughly take this form:
24
25
26
27
Where
28
correspond to the above examples from the Code.
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2
105.
If database queries were not an option, direct code could be written to access the
data. For each
something like the following checks would determine if it were a
3
If so, the
Facebook user ID could be selected:
4
5
6
7
8
9
10
106.
Users could also self-identify as class members. In anyone’s message inbox on
11
Facebook, they can go back and see their old messages. These will indicate if a URL
12
is present because it will have the URL and
13
14
15
in the message.
VII.
THE CODE FOR ANALYZING PRIVATE MESSAGES OPERATED THE SAME
FOR ALL USERS
107.
As described above, I analyzed changes in the relevant portions of the Code over
16
the time period in question. The Code for analyzing private message
operated in the same
17
way for all users. If any Facebook user with a
types in a URL to a
18
private message, Facebook will
. If the user then sends the message,
19
Facebook’s Code would
as described above.
20
21
VIII. “ORDINARY COURSE OF BUSINESS”
108.
I understand that Facebook asserts that the above-described processes are
22
employed in the “ordinary course of business.” I further understand that in the context of the
23
claims that Plaintiffs assert, an electronic communications service provider such as Facebook
24
“cannot simply adopt any revenue-generating practice and deem it “ordinary” by its own
25
subjective standard.” Campbell v. Facebook Inc., 77 F. Supp. 3d 836, 844 (N.D. Cal. 2014).
26
Instead, for an interception to fall within the scope of the defense there must be “some nexus
27
between the need to engage in the alleged interception and the subscriber’s ultimate business, that
28
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is, the ability to provide the underlying service or good.” Id. (citing In re Google Inc. Gmail
2
Litig., 2013 U.S. Dist. LEXIS 172784 (N.D. Cal. Sept. 26, 2013).
3
109.
Having reviewed Facebook’s Code and the documents provided in discovery, I
4
conclude that the interception, analysis, and use of URL
5
necessary for the functionality of message sharing in Facebook.
6
7
110.
in Private Messages is not
Facebook itself confirms this in its Interrogatory Responses, where it notes that on
some occasions a message with a URL
8
9
10
11
12
13
46
14
15
111.
Facebook goes on to explain that the URL
16
17
18
19
20
21
7
22
23
112.
The Code also shows that these steps are unnecessary. When a message is sent
24
with
25
the content of the message with its URL to the recipient.
26
27
28
are not necessary to deliver
are
45
Facebook's Second Supplemental Response and Objections to Interrogatory No. 8 at 12:3-7
(emphasis added).
46
Id. 16:24-28 (emphasis added).
47
Facebook’s Supplemental Responses and Objections to Plaintiffs’ First Set of Interrogatories at
15:10-15.
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not used to deliver the message. The
2
process. Instead, these processes are related to the acquisition of user’s Private Message content
3
for the purposes described above, such as
4
is not part of the message delivery
, and inflating engagement counts on social plugins. None of those uses fall
5
within a “nexus between the need to engage in the alleged interception and the subscriber’s
6
ultimate business, that is, the ability to provide the underlying service or good.” Campbell, 77 F.
7
Supp. 3d at 844.
8
113.
Additionally, testimony by Michael Adkins demonstrates that Facebook’s
9
10
11
private message content described above.
As explained by Michael Adkins, Facebook’s
12
13
14
For example, Mr. Adkins testified that
Facebook’s
15
16
17
18
19
20
114.
Mr. Adkins further notes that
21
22
23
24
of private message content
described above. Mr. Adkins further confirms this by explaining that
25
26
27
28
48
49
Adkins Depo. at 34:17-25.
Id. at 36:15-18.
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2
3
115.
Similarly, Mr. Adkins testified that Facebook’s
4
5
6
7
of private
8
message content described above.
9
IX.
10
“IN TRANSMISSION”
116.
I further understand that Facebook takes the position that the challenged practices
11
occurred “in storage,” as opposed to “in transmission,” and that they are therefore outside of the
12
scope of the statutes through which Plaintiffs bring their claims. My understanding is that an
13
interception must occur “contemporaneously with transmission” in order to have occurred under
14
either the Electronic Communications Privacy Act or the California Invasion of Privacy Act. In
15
re Carrier IQ, Inc., Consumer Privacy Litig., 78 F. Supp. 3d 1051, 1076 (N.D. Cal. 2015). As
16
described above, all the redirection,
17
while the Private Message is in transmission –
18
of Private Message content happens
.
19
117.
As the excerpt of the Adkins Deposition shows quoted in paragraph 30 above,52
20
the message is delivered when it is stored in the
21
message, and any URL
22
23
system. Until that point, the
; otherwise, it could not be in the
computer at all. In the testimony above, Adkins clearly describes a process by which the message
24
25
26
50
Id. at 87:16-21
27
28
52
Id. at 89:11-90:19.
Id. at 67:23-69:1.
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is
2
.53
3
118.
4
senders with URLs,
As described above, all the processing of the message, including
and count incrementing, happens before the message is
5
delivered. Thus, in my opinion, Facebook’s interception and redirection of user’s Private
6
Message content happens while the message is in transit and not while it is in storage.
7
8
Dated: November 13, 2015
9
10
__________________
11
Jennifer Golbeck
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
53
Ray He’s testimony also confirms this. See He Depo. at 206:4-6
28
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EXHIBIT A
Jennifer Golbeck
College of Information Studies (The iSchool)
University of Maryland
College Park, MD 20742, USA
E-mail: jgolbeck@umd.edu
Homepage: http://www.cs.umd.edu/∼golbeck/
1
1.A
Personal Information
University Appointments
8/2013–present
Associate Professor,
College of Information Studies (100%),
University of Maryland (College Park, Maryland)
8/2007–present
Assistant Professor,
College of Information Studies (100%),
University of Maryland (College Park, Maryland)
1.B
Education
8/2001–5/2005
University of Maryland (College Park, Maryland)
Doctor of Philosophy in Computer Science
9/1999–6/2001
University of Chicago (Chicago, Illinois)
ScientiæMagister in Computer Science
9/1995–6/1999
University of Chicago (Chicago, Illinois)
Scientiæ Baccalaureus in Computer Science
Artium Baccalaureus in Economics
1
1.C
Academic Employment Background
6/2005–8/2007
Faculty Research Associate
Institute for Advanced Computer Studies
Department of Computer Science
University of Maryland (College Park, Maryland)
8/2006–12/2006
Adjunct Professor
Computer Science Department
American University (Washington, DC)
6/2005–9/2006
Research Director
Joint Institute for Knowledge Discovery (JIKD)
University of Maryland (College Park, Maryland)
8/2001–5/2005
Research Assistant
Department of Computer Science
University of Maryland (College Park, Maryland)
8/2001–5/2005
Adjunct Lecturer
Computer Science Department
George Washington University (Washington, DC)
6/2001–5/2003
Adjunct Lecturer
Computer Science Department
Georgetown University (Washington, DC)
5/2002–8/2002
Adjunct Professor
Advanced Physics Lab
Johns Hopkins University (Laurel, Maryland)
8/2001–12/2001
Adjunct Lecturer
Computer Science Department
George Mason University (Fairfax, Virginia)
6/2000–9/2000
Visiting Graduate
Mathematics and Computer Science Division
Futures Laboratory
Argonne National Laboratory (Argonne, Illinois)
6/1999–6/2001
Lecturer
Computer Science Department
University of Chicago (Chicago, Illinois)
2
2
Research, Scholarly, and Creative Activities
• In all references, my name is in bold.
• Unless otherwise indicated, the first author is the lead author.
• Underlined names indicate students with whom I collaborated—this includes students for
whom I am/was the (co-)advisor and other students where the collaboration was limited to
specific projects.
• For work in which a student took the lead, it is customary for the student to be first author,
followed by faculty who have played an advisory or mentoring role, followed by other individuals who have contributed. In cases where a student is listed as the first author, a wavy
::::
underline indicates colleagues with whom I shared this advisory or mentoring role (to the
:::::::::
extent of my knowledge).
• References marked with α indicate that authors are listed in alphabetical order, or that all
co-authors contributed equally.
2.A
2.A.i
Books
Books Authored
B1. Jennifer Golbeck. January 2015. Introduction to Social Media Investigation: A Hands On
Approach. Syngress.
B2. Jennifer Golbeck. 2013. Analyzing the Social Web. Burlington, MA: Morgan Kaufmann.
B3. Jennifer Golbeck. 2008. Trust on the World Wide Web: A Survey. Hanover, MA: Now
Publishers Inc.
B4. Jennifer Golbeck. 2005. Art Theory for Web Design. Boston, MA: Addison–Wesley.
2.A.ii
Books Edited
B5. Jennifer Golbeck (ed). 2008. Computing with Social Trust, London, UK: Springer.
B6. K. Aberer, K.-S.Choi, N. Noy, D. Allemang, K.-I. Lee, L. Nixon, Jennifer Golbeck, P. Mika,
D. Maynard, R. Mizoguchi, G. Schreiber, P. Cudr´ -Mauroux(Eds.) The Semantic Web – 6th
e
International Semantic Web Conference, 2nd Asian Semantic Web Conference (proceedings),
Lecture Notes in Computer Science, Vol. 4825, November 2007.
2.A.iii
Chapters in Books
BC1. Jennifer Golbeck. 2015. “Who Needs an Untrustworthy Doctor? Maslow’s Hierarchy of
Needs” in The Walking Dead Psychology: Psych of the Living Dead, Travis Langley (ed.).
Sterling.
BC2. Ziegler, Cai-Nicolas, and Jennifer Golbeck. ”Models for Trust Inference in Social Networks.” Propagation Phenomena in Real World Networks. Springer International Publishing,
2015. 53-89.
3
BC3. Jennifer Golbeck, Ugur Kuter. 2008. “The Ripple Effect: Change in Trust and Its Impact
over a Social Network” in Computing with Social Trust. Jennifer Golbeck (ed.). Springer.
BC4. Jennifer Golbeck, Aaron Mannes, James Hendler, 2006. “Semantic Web Technologies for
Terrorist Network Analysis,” in Emergent Information Technologies and Enabling Policies
for Counter Terrorism. Robert Popp and John Yen (eds). Wiley-IEEE Press.
BC5. Jennifer Golbeck and Paul Mutton, 2005. “Spring-embedded Graph Visualizations of
Semantic Metadata and Ontologies,” in Visualizing the Semantic Web, 2nd Ed, Vladimir
Geroimenko, Chaomei Chen (eds.). Springer Verlag.
BC6. Jennifer Golbeck, 2004. “IRC with ChatZilla” in Paul Mutton, IRC Hacks, 2004. O’Reilly
Associates: Cambridge, MA.
BC7. Jennifer Golbeck, 2004. “IRC in Mac OS X” in Paul Mutton, IRC Hacks, 2004. O’Reilly
Associates: Cambridge, MA.
BC8. Jennifer Golbeck, 2004. “Getting Friendly with FOAFBot” in Paul Mutton, IRC Hacks,
2004. O’Reilly Associates: Cambridge, MA.
BC9. Jennifer Golbeck, 2004. “Interrogate Trust Networks with TrustBot” in Paul Mutton,
IRC Hacks, 2004. O’Reilly Associates: Cambridge, MA.
BC10. Jennifer Golbeck, 2004. “Check the Weather” in Paul Mutton, IRC Hacks, 2004. O’Reilly
Associates: Cambridge, MA.
BC11. Jennifer Golbeck, 2004. “Convert Currency” in Paul Mutton, IRC Hacks, 2004. O’Reilly
Associates: Cambridge, MA.
BC12. Jennifer Golbeck, 2004. “Don’t Get Lost in Translation” in Paul Mutton, IRC Hacks,
2004. O’Reilly Associates: Cambridge, MA.
BC13. Jennifer Golbeck, 2004. “IRC: Chatrooms for Hackers” in Rael Dornfest and James Duncan Davidson, OS X Panther Hacks, 2004. O’Reilly Associates: Cambridge, MA.
BC14. Jennifer Golbeck, Amy Alford, Ron Alford, James Hendler, 2004. “Organization and
Structure of Information using Semantic Web Technologies,” in Handbook of Human Factors in Web Design, Robert W. Proctor and Kim-Phuong L. Vu (eds.). Lawrence Erlbaum
Associates, NJ.
2.B
Articles in Refereed Journals1
J1. Jennifer Golbeck. Benford’s Law Applies to Online Social Networks. PLoS ONE. in press
3.534
J2. Irene Eleta and Jennifer Golbeck. Multilingual Use of Twitter: Social Networks at the
Language Frontier. Computers in Human Behavior. December 2014
2.489
J3. Jennifer Golbeck and Derek Hansen. A Method for Computing Political Preference Among
Twitter Followers. Social Networks. 36: 20 pages, 2014.
4.059
1
The right column indicates ISI Impact factors of the journal in the year of publication, or most recently available
impact factor otherwise. Missing values indicate that the impact factor is not available.
4
J4. Rebecca LaPlante, Judith :::::::: Jennifer Golbeck. Subject Matter Categorization of
Klavans,
::::::
Tags Applied to Digital Images from Art Museums Journal of the American Society for
Information Science and Technology. 23 pages, in press.
2.137
J5. Awalin Sopan, Manuel Freire, Meirav Taieb-Maimon, :::::::::::::::::: Jennifer GolCatherine Plaisant,
beck, and ::::::::::::::::: Exploring Data Distributions: Visual Design and Evaluation
Ben Shneiderman.
International Journal of Human-Computer Interaction, 29(2), 27 pages, 2013
0.943
J6. Jennifer Golbeck, Jes Koepfler, Beth Emmerling. An Experimental Study of Social Tagging Behavior and Image Content. Journal of the American Society for Information Science
and Technology, 62(9): 1750–1760, 2011.
2.137
J7. Jennifer Golbeck. The more people I meet, the more I like my dog: A study of petoriented social networks on the Web. First Monday, 16(2): 12 pages. 2011
J8. :::::: Watkins, I., Golbeck, J., & Huang, M. Understanding and changing older adults
Xie, B.,
perceptions and learning of social media. Educational Gerontology, (38)4: 282–296, 2011.
0.550
J9. Ugur Kuter and Jennifer Golbeck.α Using Probabilistic Confidence Models for Trust
Inference in Web-Based Social Networks. ACM Transactions on Internet Technology, 10,
2, Article 8 (June 2010), 23 pages, 2010.
2.080
J10. Jennifer Golbeck, Justin Grimes, Anthony Rogers Twitter Use by the US Congress.
Journal of the American Society for Information Science and Technology, 61(8): 1612–
162, 2010.
2.137
J11. P. T. Jaeger, J. Golbeck, A. Druin, K. R. Fleischmann. The First Workshop on the Future
of iSchool Doctoral Education: Issues, Challenges, and Aspirations. Journal of Education
for Library and Information Science, 51(3):201–208, 2010.
J12. Druin, A. Jaeger, P.T., Jennifer Golbeck., Fleischmann, K. R., Lin, J. Qu, Y., Wang,
P. & Xie, B.. The Maryland Modular Method: An Approach to Doctoral Education in
Information Studies. Journal of Education in Library and Information Science (JELIS),
50(4), 293-301, 2010.
J13. Jennifer Golbeck and Christian Halaschek-Wiener. Trust-Based Revision for Expressive
Web Syndication. Journal of Logic and Computation. 19, 5 (October 2009), 771-790.
0.821
J14. Jennifer Golbeck. Trust and Nuanced Profile Similarity in Online Social Networks. ACM
Transactions on the Web, 3, 4, Article 12, 33 pages, 2009.
2.810
J15. Jennifer Golbeck. 2008. Weaving a Web of Trust. Science 19 September 2008: 1640–
1641.
29.78
J16. James Hendler, Jennifer Golbeck. Metcalfe’s Law Applies to Web 2.0 and the Semantic
Web. Journal of Web Semantics. 6(1): 14–20, 2008.
3.410
J17. Jennifer Golbeck. The Dynamics of Web-based Social Networks: Membership, Relationships, and Change. First Monday, 12(11): 1-33, 2007.
J18. Jennifer Golbeck, James Hendler. A Semantic Web and Trust Approach to the Provenance Challenge. Concurrency and Computation: Practice and Experience, 20(5): 431–439,
2007.
5
0.535
J19. L. Moreau, B. Ludascher, I. Altintas, R. S. Barga, S. Bowers, S. Callahan, G. Chin Jr.,
B. Clifford, S. Cohen, S. Cohen-Boulakia, S. Davidson, E. Deelman, L. Digiampietri, I.
Foster, J. Freire, J. Frew, J. Futrelle, T. Gibson, Y. Gil, C. Goble, J. Golbeck, P. Groth,
D. A. Holland, S. Jiang, J. Kim, D. Koop, A. Krenek, T. McPhillips, G. Mehta, S. Miles,
D. Metzger, S. Munroe, J. Myers, B. Plale, N. Podhorszki, V. Ratnakar, E. Santos, C.
Scheidegger, K. Schuchardt, M. Seltzer, Y. L. Simmhan, C. Silva, P. Slaughter, E. Stephan,
R. Stevens, D. Turi, H. Vo, M. Wilde, J. Zhao, and Y. Zhao. The First Provenance
Challenge. Concurrency and Computation: Practice and Experience, 20(5): 409–418, 2007.
0.535
J20. Cai-Nicolas Ziegler, Jennifer Golbeck. Investigating Interactions of Trust and Interest
Similarity. Decision Support Systems, 43(2): 460–475, 2006.
1.190
J21. Richard J. Williams, Neo Martinez, Jennifer Golbeck. Ontologies for Ecoinformatics,
Journal of Web Semantics, 4(4): 237–242, 2006.
3.410
J22. Jennifer Golbeck, James Hendler. Inferring Trust Relationships in Web-Based Social
Networks, ACM Transactions on Internet Technology, 6(4): 497–529, 2006.
0.893
J23. Jennifer Golbeck, Bijan Parsia. Trust network-based filtering of aggregated claims. International Journal of Metadata, Semantics, and Ontologies, 1(1); 58–65, 2005.
J24. Jennifer Golbeck. Semantic Social Networks for Email Filtering: A Prototype and Analysis, AIS SIGSEMIS Bulletin, Vol. 2, Issue (3&4) 2005: 36–40, 2005.
J25. Frank W Hartel, Sherri de Coronado, Robert Dionne, Gilberto Fragoso, Jennifer Golbeck.
Modeling a Description Logic Vocabulary for Cancer Research. Journal of Biomedical
Informatics, 38(2): 114–129, 2005.
1.792
J26. P. Domingos, J. Golbeck, P. Mika, A. Nowak. Trends & Controversies: Social Networks
and Intelligent Systems. IEEE Intelligent Systems, 20(1): 80 – 93, 2005.
1.438
J27. Staab, Steffen, Pedro Domingos, P. Mika, Jennifer Golbeck, Li Ding, Tim Finin, Anupam
Joshi, Andrzej Nowak, and Robin R. Vallacher. Social networks applied. IEEE Intelligent
Systems, page 80-93, 2005.
J28. Aditya Kalyanpur, Jennifer Golbeck, Jay Banerjee, James Hendler. OWL: Capturing
semantic information using a standardized web ontology language. Multilingual Computing
& Technology, 15(7): 8 pages, 2004.
J29. Leslie E. Chipman, Benjamin B. Bederson, Jennifer Golbeck. SlideBar: Analysis of a
linear input device. Behaviour and Information Technology, 23(1): 1–9, 2004.
1.028
J30. Jennifer Golbeck, Gilberto Fragoso, Frank Hartel, Jim Hendler, Jim Oberthaler, Bijan
Parsia. The National Cancer Institute’s Thesaurus and Ontology. Journal of Web Semantics, 1(1): 75–80, 2004.
3.410
2.C
Monographs, Reports, and Extension Publications
R1. Aditya Kalyanpur, James Hendler, Bijan Parsia, Jennifer Golbeck.
markup, ontology, and RDF editor. 2006.
SMORE-semantic
R2. Jennifer Golbeck. Computing and Applying Trust in Web-based Social Networks, Ph.D.
Thesis, University of Maryland, College Park, 2005.
R3. Jennifer Golbeck. Genetic Algorithms for Strategic Optimization. Master’s Thesis, University of Chicago, 2001.
6
2.D
Book Reviews, Other Articles, and Notes
1. “Data Meets Design: a Review of Judith Donath’s The Social Machine”
Science, January 15, 2015
2. “The Live-Tweeted Prostitution Sting Was a Total Bust, and Not in a Good Way”
Slate, May 7, 2014
3. “What a Toilet Hoax Can Tell Us About the Future of Surveillance, on The Atlantic”
The Atlantic, April 29, 2014
4. “Google Tweaked How It Displays Search Results. Heres How to Change It Back”
Slate, March 14, 2014 Slate, January 1, 2014
5. “Beacon, ShopKick: Privacy Policies for location-tracking apps arent clear enough”
Slate January 28, 2014
6. “Facebook Cleansing: How to delete all of your account activity”
Slate, January 1, 2014
7. “Facebook self-censorship: What happens to the posts you don’t publish”
Slate, December 13, 2013
8. “Lovely Spam! Wonderful Spam! (book review of Spam A Shadow History of the Internet)”
Science: Vol. 340 no. 6137 p. 1171, 7 June 2013
2.E
2.E.i
Talks, Abstracts, and Other Professional Papers Presented
Invited Talks: Keynote (and Similar) Addresses
T1. “Privacy, Social Context, and Social Media”
TEDxUMD
College Park, MD (May 3, 2014)
T2. “Trust and Social Media”
AAAI 2013 Fall Symposium Series (Keynote)
Arlington, VA (November 15-17, 2013)
T3. “Hidden Information Uncovered”
TEDxMidAtlantic
Washington, DC (October 25, 2013)
T4. “User Profiling: a two-sided argument”
Conference on Social Computing and Its Applications (Keynote)
Karlsruhe, Germany (October 2, 2013)
T5. “Analyzing the Social Web”
Baltimore Data Day, Federal Reserve Bank of Richmond (Keynote)
Baltimore, MD (July 11, 2013)
T6. “Uncovering Hidden Social Information”
Data Science DC
Washington, DC (March 28, 2013)
7
T7. “Pets on the Internet”
TEDxGeorgetown
Washington, DC (March 23, 2011)
T8. “Tutorial on Using Social Trust for Recommender Systems”
ACM Conference on Recommender Systems (RecSys ’09)
New York, New York (October 22, 2009)
T9. “Computing with Social Trust: Web Algorithms, Social Networks, and Recommendations”
Haverford College Distinguished Visitors Program, and Fantastic Lectures in Computer Science
Series
Haverford, Pennsylvania (March 17, 2009)
T10. “Social Recommender Systems”
SONIC and NICO Lecture Series, Northwestern University
Evanston, Illinois (November 12, 2008)
T11. “The Dynamics of Web-based Social Networks: Membership, Relationships, and Change”
International Sunbelt Social Networking Conference (Sunbelt XXVIII)
St. Pete, Florida (January 22, 2008)
T12. “Social Networks, the Semantic Web, and the Future of Online Scientific Collaboration”
FermiLab Colloquium Lecture
Batavia, Illinois (October 25 2006)
T13. “Trust and Web Policy Systems”
Keynote talk at the Second International Workshop on the Value of Security through Collaboration
Baltimore, Maryland (September 1, 2006)
2.E.ii
2.E.ii.1
Refereed conference proceedings
Papers at Top-Tier Conferences
1
C1. Kan-Leung Cheng and I Zuckerman and D Nau, and J Golbeck ”Predicting Agents Behavior by Measuring their Social Preferences.” Proceedings on the European Conference
on Artificial Intelligence. (2014).
C2. Tammar Shrot, Avi Rosenfeld, Jennifer Golbeck, Sarit Kraus. Timing Interruptions to
Improve User Performance. In Proceedings of the ACM Conference on Human Factors in
Computing Systems (CHI’14). 10 pages. April 2014, Toronto, Canada
23%
C3. Jennifer Golbeck, Eric Norris. Personality, Movie Preferences, and Recommendations. In
Proceedings of the International Conference on Advances in Social Network Analysis and
Mining, 4 pages. August 2013, Niagra Falls, Canada.
15%
C4. Bert Huang, Angelika Kimmig and Lise Getoor and Jennifer Golbeck. Flexible Framework for Probabilistic Models of Social Trust. In 2013 Conference on Social Computing,
Behavioral Modeling and Prediction, 9 pages. April 2013, College Park, MD
31%
1
Conferences with highly-selective acceptance rates and/or top reputations in their field.
8
C5. Carman Neustaedter and Jennifer Golbeck. Exploring pet video chat: the remote awareness and interaction needs of families with dogs and cats. In Proceedings of Computer
Supported Cooperative Work (CSCW’13), in press, 6 pages. February 2013, San Antonio,
TX
C6. Jennifer Golbeck. The Twitter Mute Button: A Web Filtering Challenge. In Proceedings
of the 30th International Conference on Human Factors in Computing Systems (CHI ’12),
pages 2755–2758. May 2012, Austin, TX.
23%
C7. Irene Eleta and Jennifer Golbeck. A Study of Multilingual Social Tagging of Art Images:
Cultural Bridges and Diversity. In Proceedings of Computer Supported Cooperative Work
(CSCW’12), pages 695–704. February 2012, Seattle, Washington
40%
C8. Cheng, K.L., Zuckerman, I., Nau,::: and Golbeck, J. The Life Game: Cognitive StrateD.,
::::
gies for Repeated Stochastic Games. In IEEE Third International Conference on and 2011
IEEE Third International Conference on Social Computing (SocialCom), pages 495-102.
October 2011, Boston, Massachusetts.
10%
C9. Nicholas Violi, Jennifer Golbeck, Kan-leung Cheng, and Ugur Kuter. Caretaker: A
Social Game for Studying Trust Dynamics. In IEEE Third International Conference on
and 2011 IEEE Third International Conference on Social Computing (SocialCom), pages
451–456. October 2011, Boston, Massachusetts.
10%
C10. J. Golbeck, C. Robles, M. Edmondson, and K. Turner. Predicting personality from twitter. In IEEE Third International Conference on and 2011 IEEE Third International Conference on Social Computing (SocialCom), pages 149–156. October 2011, Boston, Massachusetts.
10%
C11. K.L. Cheng, U. Kuter, and J. Golbeck. Coevolving strategies in social-elimination games.
In IEEE Third International Conference on and 2011 IEEE Third International Conference
on Social Computing (SocialCom), pages 118–126. October 2011, Boston, Massachusetts.
10%
C12. Thomas Dubois, Jennifer Golbeck, and ::::::::::::::::::: Network Clustering ApAravind Srinivasan.
proximation Algorithm Using One Pass Black Box Sampling. In Third IEEE International
Conference on Social Computing (SocialCom), pages 418–424. October 2011, Boston, Massachusetts. (Best Paper Award).
10%
C13. Thomas Dubois, Jennifer Golbeck, and ::::::::::::::::::: Predicting Trust and DisAravind Srinivasan.
trust in Social Networks. In Third IEEE International Conference on Social Computing
(SocialCom), pages 418–424. October 2011, Boston, Massachusetts.
10%
C14. Jennifer Golbeck and Derek Hansen. Computing Political Preference Among Twitter
Followers. In Proceedings of the 29th International Conference on Human Factors in Computing Systems (CHI ’11), pages 1105–1108. April 2011, Vancouver, Canada.
23%
C15. Greg Walsh and Jennifer Golbeck Curator: a game with a purpose for collection recommendation. In Proceedings of the 28th international Conference on Human Factors in
Computing Systems (CHI ’10), pages 2079–2082. April 2010, Atlanta, Georgia.
22%
C16. Freire, M., Plaisant, C., Shneiderman, B., and Golbeck, J. ManyNets: an interface for
multiple network analysis and visualization. In Proceedings of the 28th international Conference on Human Factors in Computing Systems (CHI ’10), pages 213–222. Atlanta,
Georgia, USA, April 10–15, 2010.
22%
9
C17. Ugur Kuter, Jennifer Golbeckα . Semantic Web Service Composition in Social Environments. Proceedings of the International Semantic Web Conference (ISWC09), pages
344–358. November 2009, Washington, D.C. (Best Paper Award)
20%
C18. Thomas DuBois, Jennifer Golbeck, ::::::::::::::::::: Rigorous Probabilistic Trust InAravind Srinivasan.
ference with applications to clustering. Proceedings of the IEEE/WIC/ACM International
Conference on Web Intelligence, pages 655–658. September 2009, Milan Italy.
18%
C19. Derek Hansen, Jennifer Golbeck. Mixing it Up: Recommending Collections of Items.
Proceedings of the Conference on Human Factors in Computing Systems (CHI’09), pages
1217–1226. April 2009, Boston, Massachusetts.
24.5%
C20. Jennifer Golbeck, Matthew Rothstein. Linking Social Networks on the Web with FOAF:
A Semantic Web Case Study. Proceedings of the Twenty-Third National Conference on
Artificial Intelligence (AAAI-08), pages 1138–1143. July 2008, Chicago, Illinois.
24%
C21. Ugur Kuter and Jennifer Golbeckα . SUNNY: A New Algorithm for Trust Inference in
Social Networks, using Probabilistic Confidence Models. Proceedings of the Twenty-Second
National Conference on Artificial Intelligence (AAAI-07), pages 1377–1382. July 2007,
Vancouver, Canada.
27%
C22. Yarden Katz and Jennifer Golbeck. Social Network-based Trust in Prioritized Default
Logic. Proceedings of The Twenty-First National Conference on Artificial Intelligence
(AAAI-06), pages 1345–1350. July 2006, Boston, Massachusetts.
30%
C23. Jennifer Golbeck, James Hendler. Inferring reputation on the semantic web. Proceedings
of the 13th International World Wide Web Conference, 8 pages. May 2004. New York, NY.
14.6%
C24. Jennifer Golbeck, Michael Grove, Bijan Parsia, Aditya Kalyanpur, and James Hendler.
New Tools for the Semantic Web, Proceedings of the 13th International Conference on
Knowledge Engineering and Knowledge Management (EKAW 2002), pages 392–400. October 2002, Siguenza, Spain.
34%
2.E.ii.2
Papers at Other Conferences
C25. Cody Buntain and Jennifer Golbeck. ”Identifying social roles in reddit using network
structure.” Proceedings of the companion publication of the 23rd international conference
on World wide web companion. International World Wide Web Conferences Steering Committee, 2014.
C26. Greg Walsh and Jennifer Golbeck. 2014. StepCity: a preliminary investigation of a
personal informatics-based social game on behavior change. In CHI ’14 Extended Abstracts
on Human Factors in Computing Systems (CHI EA ’14). ACM, New York, NY, USA, 23712376.
C27. Sibel Adali and Jennifer Golbeck. Predicting personality with social behavior. In 2012
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 8 pages. August 2012, Istanbul, Turkey.
C28. Buntain,Cody, Jennifer Golbeck, Dana::::::::::::::::::::::: Advice and Trust in
Nau, and Sarit Kraus.
:::::
Games of Choice. In Tenth Annual Conference on Privacy, Security and Trust, 2 pages.
July 2012, Paris, France.
10
C29. Jennifer Golbeck, Hal Warren, and Eva Winer. Making trusted attribute assertions
online with the publish trust framework. In Tenth Annual Conference on Privacy, Security
and Trust, 2 pages. July 2012, Paris, France.
C30. David Yates and Jennifer Golbeck. Is facebook appropriate for the classroom? a comparison of student and faculty perspectives. In Proceedings of the Euro-American Conference
for Academic Disciplines and Creativity, 27 pages. June 2012, Prague, Czech Republic.
(Outstanding Research Presentation).
C31. Jennifer Golbeck. STEM initiatives for improved communication skills in the zombie
apocalypse. In Proceedings of the 2012 ACM Conference on Human Factors in Computing
Systems Extended Abstracts, pages 1425–1426. May 2012, Austin, TX.
C32. Jennifer Golbeck and Carman Neustaedter. Pet video chat: monitoring and interacting
with dogs over distance. In Proceedings of the 2012 ACM Conference on Human Factors
in Computing Systems Extended Abstracts, pages 1425–1426. May 2012, Austin, TX.
C33. Jennifer Golbeck, Cristina Robles, Karen Turner Predicting Personality with Social Media. Proceedings of alt.chi, ACM Conference on Human Factors in Computing (CHI 2011),
pages 253–262. April 2011, Vancouver, Canada.
C34. James Michaelis, Jennifer Golbeck, ::::::::::::::: Leveraging the Semantic Web to
James Hendler
Enable Content Mashup For End Users. Proceedings of HCI International 2011, 10 pages.
July 2011, Orlando, Florida.
C35. Jennifer Golbeck, Kenneth Fleischmann. Trust in Social Q &A: The Impact of Text
and Photo Cues of Expertise. Proceedings of ASIST 2010, pages 1–10. October 2010,
Pittsburgh, Pennsylvania.
C36. Klavans, Judith, Jennifer Golbeck. Integrating Multiple Computational Techniques for
Improving Image Access: Applications to Digital Collections. Proceedings of the 2010 Grace
Hopper Conference, 5 pages. September 2010, Atalanta, Georgia.
C37. Dana Rotman, Jennifer Golbeck, ::::::::::::::: The Community is Where the Rapport
Jennifer Preece.
Is: On Sense and Structure in the YouTube Community. 2009 Communities & Technologies
Conference, pages 41–50. June, 2009. University Park, Pennsylvania.
C38. Jennifer Golbeck. On the Internet, Everybody Knows You’re a Dog: The Human-Pet
Relationship in Online Social Networks. ACM Conference on Human Factors in Computing
Systems Extended Abstracts, pages 4495-4500. April 2009, Boston, Massachusetts.
C39. Jennifer Golbeck, Michael Wasser. SocialBrowsing: Integrating Social Networks into Web
Browsing. ACM Conference on Human Factors in Computing Systems Extended Abstracts,
pages 2381–2386. April 2007, San Jose, California.
C40. Aaron Mannes, Jennifer Golbeck. Ontology Building: A Terrorism Specialist’s Perspective. Proceedings of the IEEE Aerospace Conference, 5 pages. March 2007, Big Sky,
Montana.
C41. Aaron Mannes, Jennifer Golbeck. Building a Semantic Web Portal for Counterterror
Analysis. Proceedings of the IEEE Aerospace Conference, 5 pages. March 2007, Big Sky,
Montana.
C42. Jennifer Golbeck, Computing with Trust: Definition, Properties, and Algorithms. Proceedings of International Conference on Security and Privacy in Communication Networks,
pages 1-7. August 2006, Baltimore, Maryland.
11
C43. Jennifer Golbeck. Generating Predictive Movie Recommendations from Trust in Social
Networks. Proceedings of the Fourth International Conference on Trust Management, pages
93–104. May 2006, Pisa, Italy.
C44. Jennifer Golbeck, James Hendler. FilmTrust: Movie recommendations using trust in
web-based social networks. Proceedings of the IEEE Consumer Communications and Networking Conference, pages 497–529. January 2006, Las Vegas, Nevada.
C45. Jennifer Golbeck, Bernardo Cuenca Grau, Christian Halaschek-Wiener, Aditya Kalyanpur, Yarden Katz, Bijan Parsia, Andrew Schain, Evren Sirin, and James Hendler. Semantic
web research trends and directions. Proceedings of the First international Conference on
Pattern Recognition and Machine Intelligence, PReMI. 2005, pages 160-169. December
2005, Kolkata, India.
C46. Jennifer Golbeck, James Hendler. Accuracy of Metrics for Inferring Trust and Reputation in Semantic Web-based Social Networks, Proceedings of 14th International Conference
on Knowledge Engineering and Knowledge Management, pages 116–131. October 2004,
Northamptonshire, UK.
C47. Jennifer Golbeck, James Hendler. Reputation Network Analysis for Email Filtering.
Proceedings of the First Conference on Email and Anti-Spam, pages 54–58. July 2004,
MountableView, California.
C48. Jennifer Golbeck, Bijan Parsia, James Hendler. Trust Networks on the Semantic Web,
Proceedings of Cooperative Information Agents, pages 238–249. August 2003, Helsinki,
Finland.
C49. Mutton, Paul and Jennifer Golbeck. Visualization of Semantic Metadata and Ontologies,
Proceedings of Information Visualization, pages 300–305. July 2003, London, UK.
C50. Kalyanpur, Aditya and Jennifer Golbeck and Michael Grove and Jim Hendler. 2002.
An RDF Editor and Portal for the Semantic Web, Proceedings of Semantic Authoring,
Annotation & Knowledge Markup (ECAI 2002), 4 pages. July 2002, Lyon, France.
C51. Jennifer Golbeck. Evolving Strategies for the Prisoner’s Dilemma, Advances in Intelligent Systems, Fuzzy Systems, and Evolutionary Computation, pages 299–306. February
2002, Interlaken, Switzerland.
2.E.iii.3
Papers at Refereed Workshops
W1. Jennifer Golbeck, Thameem Khan, Nilay Sanghavi and Nishita Thakker. Multiple Personalities on the Web: A Study of Shared Mboxes in FOAF. Proceedings of the 2009 Workshop
on Social Data on the Web, 12 pages. October 2009, Washington, DC.
W2. Thomas DuBois, Jennifer Golbeck, John Kleint, ::::::::::::::::::: Improving RecomAravind Srinivasan.
mendation Accuracy by Clustering Social Neworks with Trust. Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems and the Social Web, 8 pages. October 2009,
New York, New York.
W3. Audun Josang, Jennifer Golbeck, Challenges for robust trust and reputation systems. Proceedings of the 5th International Workshop on Security and Trust Management. 12 pages.
August, 2009, Saint Malo, France.
12
W4. Elena Zheleva, Jennifer Golbeck, Lise ::::::: Ugur Kuter. Using Friendship Ties and
Getoor,
::::
Family Circles for Link Prediction. SNA-KDD Workshop on Social Network Mining and
Analysis, pages 97-113. August 2008, Las Vegas, Nevada.
W5. V. Shiv Naga Prasad, Behjat Siddiquie, Jennifer Golbeck, and :::::::::::::: Classifying
Larry S. Davis.
Computer Generated Charts. In Proceedings of the Workshop on Content Based Multimedia
Indexing, pages 85-92. June 2007, Bordeaux, France.
W6. Jennifer Golbeck, Aaron Mannes. Using Trust and Provenance for Content Filtering on
the Semantic Web. Proceedings of the Workshop on Models of Trust on the Web, 9 pages.
May 2006, Edinburgh, UK.
W7. Christian Halaschek-Wiener, Jennifer Golbeck, Bijan Parsia, Vladimir Kolovski, and ::::
Jim
Hendler. Image browsing and natural language paraphrases of semantic web annotations.
:::::::
First International Workshop on Semantic Web Annotations for Multimedia (SWAMM), 12
pages. May 2006, Edinburgh, UK.
W8. Christian Halaschek-Wiener, Jennifer Golbeck, Andrew Schain, Michael Grove, Bijan Parsia,
and :::::::::::: Annotation and provenance tracking in semantic web photo libraries. ProJim Hendler.
ceedings of the International Provenance and Annotation Workshop, pages 82–89. May 2006,
Chicago, Illinois.
W9. Jennifer Golbeck. Combining Provenance with Trust in Social Networks for Semantic Web
Content Filtering. Proceedings of the International Provenance and Annotation Workshop,
pages 101–108. May 2006, Chicago, Illinois.
W10. Yarden Katz and Jennifer Golbeck. Nonmonotonic Reasoning with Web-Based Social Networks. Proceedings of the Workshop on Reasoning on the Web, pages 469–475. May 2006,
Edinburgh, UK.
W11. Aaron Mannes, Jennifer Golbeck, James Hendler. Semantic Web and Target-Centric Intelligence: Building Flexible Systems that Foster Collaboration. Proceedings of Workshop
Intelligent User Interfaces for Intelligence Analysis, 4 pages. January 2006, Sydney, Australia.
W12. Jennifer Golbeck. Semantic Web Interaction through Trust Network Recommender Systems. End User Semantic Web Interaction Workshop, pages 327–339. November 2005, Sanibel
Island, Florida.
W13. Jennifer Golbeck. Personalizing Applications through Integration of Inferred Trust Values
in Semantic Web-Based Social Networks. Semantic Network Analysis Workshop, pages 1005–
1018. November 2005, Sanibel Island, Florida.
W14. Bijan Parsia, Taowei Wang, and Jennifer Golbeck. Visualizing Web Ontologies with CropCircles. End User Semantic Web Interaction Workshop, pages 1–8. November 2005, Sanibel
Island, Florida.
W15. Christian Halaschek-Wiener, Andrew Schain, Jennifer Golbeck, Michael Grove, Bijan Parsia, Jim Hendler. A flexible approach for managing digital images on the semantic web.
5th International Workshop on Knowledge Markup and Semantic Annotation, pages 49–58.
November 2005, Galway, Ireland.
13
W16. Kalyanpur, Aditya, Nada Hashmi, Jennifer Golbeck, Bijan Parsia. Lifecycle of a Casual
Web Ontology Development Process. Proceedings of the Workshop on Application Design,
Development and Implementation Issues in the Semantic Web, 8 pages. May 2004, New
York, New York.
W17. Jennifer Golbeck, Paul Mutton, Semantic Web Interaction on Internet Relay Chat, Proceedings of Interaction Design on the Semantic Web, 5 pages. May 2004, New York, New
York.
2.E.iii.4
Refereed Posters2
P1. Irena Eleta and Jennifer Golbeck. Bridging Languages in Social Networks: How Multilingual
Users of Twitter Connect Language Communities?, ASIS&T 2012 Annual Meeting, October
2012, Baltimore, Maryland.
P2. Bert Huang and Angelika Kimmigand Lise Getoor and Jennifer Golbeck. Probabilistic Soft
Logic for Trust Analysis in Social Networks, International Workshop on Statistical Relational
AI. August 2012, Catalina Island, CA.
P3. Cristina Robles, Jennifer Golbeck. Facebook Relationships in the Workplace. Proceedings
of CompleNet 2012. March 2012, Marathon, Florida.
L. Klavans,
Dagobert Soergel,
P4. Judith:::::::::::: Susan Chun, Jennifer Golbeck, ::::::::::::::::: Robert Stein, Ed
::::::
Bachta, Rebecca LaPlante, Kate Mayo, John Kleint. Language and Image: T3 = Text, Tags,
and Trust. 2009 Digital Humanities Conference. July 2009, College Park, Maryland.
P5. Jennifer Golbeck, Jeanne Kramer-Smyth. Visualizing Archival Collections with ArchivesZ.
Proceedings of the 2009 Digital Humanities Conference, July 2009, College Park, Maryland.
P6. Praveen Paruchuri, Preetam Maloor, Bob Pokorny, Aaron Mannes, Jennifer Golbeck. Cultural Modeling in a Game-Theoretic Framework, AAAI Fall Symposium on Adaptive Agents
in Cultural Contexts. November 2008, Washington, DC.
P7. Wu, P. F., Qu, Y., Fleischmann, K., Golbeck, J., Jaeger, P., Preece, J., & Shneiderman,
B. Designing a Community-Based Emergency Communication System: Requirements and Implications. Annual Meeting of the American Society for Information Science and Technology
(ASIS&T 2008). October 2008, Columbus, OH.
P8. Jennifer Golbeck, FilmTrust: Movie Recommendations from Semantic Web-based Social
Networks. IEEE Consumer Communications and Networking Conference. January 2006, Las
Vegas, Nevada.
P9. Jennifer Golbeck, FilmTrust: Movie Recommendations from Semantic Web-based Social
Networks. International Semantic Web Conference. November 2005, Galway, Ireland
P10. Halaschek-Wiener, Christian , Jennifer Golbeck, Andrew Schain, Michael Grove, Bijan Parsia,
Jim HendlerPhotostuff-an image annotation tool for the semantic web. Proceedings of the
Poster Track, 4th International Semantic Web Conference. November 2005, Galway, Ireland.
2
Peer-reviewed poster presentations, typically accompanied by short descriptions in associated proceedings.
14
P11. Pin Xu, Lyubov Remennik, N. Rao Thotakura, Jennifer Golbeck, Liju Fan. Prototype
development of an immunology ontology that integrates multiple biomedical ontologies. 7th
International Protege Conference. July 2004, Washington, DC.
P12. Jennifer Golbeck, Bijan Parsia, James Hendler. Trust Networks on the Semantic Web.
Twelfth International World Wide Web Conference, May 2003, Budapest, Hungary.
P13. Jennifer Golbeck, Ron Alford, Ross Baker, Mike Grove, Jim Hendler, Aditya Kalyanpur,
Amy Loomis, Ron Reck. Semantic Web Tools from MINDSWAP. 1st Annual International
Semantic Web Conference, June 2002, Sardinia, Italy.
2.I
Fellowships, Prizes, and Awards
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•
2.J
2.J.i
2015 University of Maryland Research Communication Award
2014 University System of Maryland Board of Regents Mentoring Award
TED Most Powerful Talks of 2014
2011 IEEE Conference on Social Computing Best Paper Award
2009 International Semantic Web Conference Best Paper Award
Research Fellow, Web Science Research Initiative (2008 – present)
IEEE Intelligent Systems Ten to Watch3 (May 2006)
2005 DARPA IPTO Young Investigator (May 2005)
Editorships, Editorial Boards, and Reviewing Activities for Journals and
Other Learned Publications
Editorial Boards
• Editorial Board, Data Science
• Editorial Committee, Journal of Web Semantics – Special Issue “Exploring New Interaction
Designs Made Possible by the Semantic Web”
• Guest Editor, Security & Privacy Magazine, Special Issue on “Security in Social Networks”
2.J.ii
•
•
•
•
•
•
•
•
•
3
Conference Chair Positions
Program Co-chair, Recsys 2015: Conference on Recommender Systems
Fellowships Chair, ISWC 2012: 11th International Semantic Web Conference
Fellowships Chair, ISWC 2011: 10th International Semantic Web Conference
Tutorials Co-chair, Program Committee Vice Chair, ISWC 2009: 8th International Semantic
Web Conference
Co-organizer, SWUI 2009: Semantic Web User Interactions: Exploring HCI Challenges
Workshop at ISWC09.
Co-organizer, Workshop on Social Technology for Biodiversity: Motivation, Credibility &
Community, 2008
Co-organizer, SWUI 2008: Semantic Web User Interactions: Exploring HCI Challenges
Workshop at CHI’08
Semantic Web Challenge Co-chair, ISWC 2007: 6th International Semantic Web Conference
Semantic Web Challenge Co-chair, ASWC 2007: 2nd Asian Semantic Web Conference
list of top ten young AI researchers
15
•
•
•
•
Co-organizer, Helping Users Make Sense of Social Networks: A Workshop, 2007
Proceedings Chair, ISWC 2006: 5th International Semantic Web Conference
Co-organizer, Workshop on Trust, Security, and Reputation on the Semantic Web, 2006
Organizer, Developers Day Trust on the Web Track, WWW 2005: 13th International World
Wide Web Conference
2.J.iii
Reviewing: Journals
•
•
•
•
•
•
•
•
•
•
•
•
•
ACM Computing Surveys: 2012 (1)
ACM Transactions on Intelligent Systems: 2012 (2)
ACM Transactions on Internet Technology: 2009 (1)
ACM Transactions on Multimedia Computing, Communications, and Applications: 2009 (1)
ACM Transactions on the Web: 2008 (2), 2009(1), 2012 (1)
Behaviour and Information Technology: 2008 (1)
Artificial Intelligence: 2008 (1)
European Journal of Operational Research: 2007 (1)
Foundations and Trends in Information Retrieval: 2015 (1)
Foundations and Trends in Web Science: 2013 (1),
International Journal of Human Computer Studies: 2008 (1)
International Journal on Semantic Web and Information Systems: 2007 (1)
Journal of the American Society for Information Science and Technology: 2010 (1), 2011 (1),
2012 (1)
• Journal of Web Semantics: 2006 (1), 2007 (3), 2008 (1), 2012 (2)
• Policy & Internet: 2012 (1)
2.J.iv
Reviewing: Top-Tier Conferences
• AAAI: AAAI Conference on Artificial Intelligence, Senior Program Committee 2011, 2012;
Program Committee 2006, 2007, 2008, 2009, 2010
• RecSys: ACM Conference on Recommender Systems, Senior Program Committee 2010,
2011, 2012
• CSCW: Computer Supported Cooperative Work, Program Committee 2008, 2012, 2013
• CHI: ACM Conference on Human Factors in Computing, Program Committee 2009, 2010,
2011, 2012
• IJCAI, International Joint Conference on Artificial Intelligence, Program Committee 2009
• WWW: International World Wide Web Conference, Program Committee 2006, 2007, 2008,
2009
• ISWC: International Semantic Web Conference, Senior Program Committee 2009, 2010,
2011, 2012, Program Committee 2008
• KDD: Conference on Knowledge Discovery and Data Mining, Senior Program Committee
2010
• GROUP: Conference on Supporting Group Work, Program Committee 2009
• IJCAI: International Joint Conferences on Artificial Intelligence, Program Committee 2009
2.J.v
Reviewing: Other Venues
• IFIPTM: International Conference on Trust Management, Program Committee 2009, 2010,
2011, 2012
• IEA-AIE: Engineering Knowledge and Semantic Systems, Program Committee 2011
16
• SSW: AAAI Symposium on the Social Semantic Web, Program Committee: 2009
• WebSci: Web Science Conference: Society On-Line International Semantic Web Conference,
Program Committee 2008
• BlogTalk: International Conference on Social Software, Program Committee 2008
• PST: Conference on Privacy, Security and Trust, Program Committee 2008
• SAC: ACM Symposium on Applied Computing, Program Committee 2008, 2005
• CoSoSo: International Conference on Social Software, Program Committee 2008
• IUI: Intelligent User Interfaces Conference, Program Committee 2008
• CEAS: Conference on Email and Anti-Spam, Program Committee 2007
• CIKM: onference on Information and Knowledge Management, Program Committee 2007
• CAT: Context Awareness and Trust, Program Committee 2007
• Policy: IEEE Policy, Program Committee 2007
• SWC: Semantic Web Challenge, Program Committee 2007
• SCCSW: Social and Collaborative Construction of Structured Knowledge Workshop, Program Committee 2007
• SWCKA: AAAI Fall Symposium on Semantic Web for Collaborative Knowledge Acquisition,
Program Committee 2006
• EKAW: International Conference on Knowledge Engineering and Knowledge Management,
Program Committee 2006
• SECOVAL: The Value of Security through Collaboration Workshop, Program Committee
2005, 2006.
• SWUI: Semantic Web User Interaction Workshop, Program Committee 2006
• OWLED: OWL Experiences and Directions, Program Committee 2006
• SPTWS: Workshop on Security, Privacy, and Trust in Web Services, Program Committee
2006
• MTW: Models of Trust Workshop, Program Committee 2006
• OWLED: OWL: Experiences and Directions Workshop, Program Committee 2005
• FOAF: Workshop on Friend of a Friend, Social Networking, and the Semantic Web, Program
Committee 2004
• SWUI: First International Workshop on Interaction Design and the Semantic Web, Program
Committee 2004
• VIKE: Visualizing Information in Knowledge Engineering (VIKE), Program Committee 2003
2.K
2.K.i
Other
External Talks (see section 2.E.i for keynote and similar talks)
• “Opportunities and risks of discovering personality traits from social media”
CHI 2014
Toronto, Canada (May 29, 2014)
• “Predicting User Attributes in Social Media ”
Society 2013
State College, PA (May 9, 2013)
• “Generational Computing and Social Media”
Department of Defense Deep Dive on Obesity
Portsmouth, VA (August 19, 2012)
• “Information Sharing in Social Networks”
FBI Lookout Group Meeting
17
Dallas, TX (August 14, 2012)
• “Social Networks and HCI Research”
National Reconnaissance Office
Chantilly, VA (March 15, 2012)
• “Information Sharing in Social Networks”
Potomac Valley Chapter (PVC) of the American Society of Information Science and Technology
Washington, DC (April 10, 2012)
• “Computing Trust and Personality in Social Networks”
Aberdeen Proving Ground Network Science Meeting
Aberdeen, MD (March 5, 2012)
• “Managing Content With Trust’
Professional & Scholarly Publishers 2012 Annual Conference
Washington, DC (February 2, 2012)
• “Information Sharing in Social Networks”
FBI Lookout Group Meeting
Dallas, TX (January 9, 2012)
• “From Open Data to Open Worlds: The Power of the Semantic Web” World Bank Information
Management Technology Group Forum
Washington, DC (December 8, 2011)
• “Information Sharing in Social Networks”
FBI Headquarters – Counterintelligence Division All-hands Meeting
Washington, DC (November 17, 2011)
• “Predicting Personality from Social Media”
FBI Counterintelligence Behavioral Analysis Unit
Quantico, VA (November 1, 2011)
• “Computing with Social Trust”
Army Research Lab Seminar Series
Adelphi, MD (December 8, 2010)
• “Computing with Social Trust”
Aberdeen Proving Ground CTA Seminar
Aberdeen, MD (November 16, 2010)
• “Personality Traits and Facebook Profiles”
Social and Cognitive Network Academic Research Center Seminar Series
Rensselaer Polytechnic Institute, Troy, NY (April 18, 2010)
• “Social Recommender Systems on the Semantic Web”
National Archives Semantic Web Myth and Fact
Washington, DC (November 17, 2009)
• “Social Software in Digital Libraries and Archives”
Online Computer Library Center (OCLC)
Arlington, VA (November 5, 2009)
• “Recommender Systems, Social Trust, and Television Applications”
StreamSage (a division of Comcast)
Washington, DC (September 9, 2009)
• “Social Networks on the Semantic Web”
Microsoft Research Faculty Summit
Redmond, Washington (July 28, 2008)
• “Understanding Social Networks”
18
•
•
•
•
The 25th Annual Human-Computer Interaction Lab Symposium
College Park, Maryland (May 29, 2008)
“Social Networks and Intelligent Systems: Using Relationships for Information Access”
University of Illinois Urbana-Champaign HCI Seminar
Urbana, Illinois (February 29, 2008)
“Social Networks and the Semantic Web”
Invited talk at Rensselaer Polytechnic Institute
Troy, New York (February 4, 2008)
“Recommending Movies with Social Networks”
Streamsage / Comcast
Washington, DC (November 2007)
“Social Information Access: Connecting Distributed Information and People on the Web”
Presentations with similar titles and content given in the following venues
– Northeastern University College of Computer and Information Science
Boston, Massachusetts (February 2007)
– University of Maryland College of Information Studies
College Park, Maryland (February 2007)
– Drexel College of Information Science and Technology
Philadelphia, Pennsylvania (April 2007)
• “Analysis and Applications of Web-based Social Networks”
University of Illinois at Urbana-Champaign Age of Networks: Social, Cultural, and Technological Connections Speaker Series
Urbana, Illinois (January 22 2007)
• “Provenance Challenge: A Semantic Web Approach”
Global Grid Forum – GGF18/GridWorld
Washington, DC (September 13 2006)
• “The Other Kind of Networking: Social Networks on the Web”
Duke University (March 2006)
• Web-based Social Network Analysis for Socially Intelligent Applications
University of Illinois at Chicago (November 2005)
• “Trust in Social Networks”
National Security Agencys Knowledge Discovery Research Colloquium
Ft. Meade, Maryland (August 2005)
• “Connections, Computation, and Cinema”
Presentations with similar titles and content given in the following venues
– University of Georgia, March 2005.
– MIT Media Lab, March 2005.
• “Inferring Trust in Web-based Social Networks”
National Security Agency
Ft. Meade, Maryland (February 2005)
• “Trust on the Semantic Web”
Thirteenth Annual World Wide Web Conference Developers Day
New York, New York (May 2004)
• “The Semantic Web as a Complex System”
International Conference on Complex Systems
Boston, Massachusetts (May 2004)
19
• “Metadata Visualization Challenges”
NASA Goddard Semantic Web Interest Group
Greenbelt, Maryland (November 2003)
• “Semantic Web: Structure and Modeling”
Half-day workshop at the Howard University
Washington, DC (June 2003)
• “Putting Time into Cognitive Systems: From Real-Time Operating Systems to Information
Dynamics”
Virtual Worlds and Simulation Conference
Orlando, Florida (January 2003)
• “Tools on the Semantic Web”
Half-day workshop at the Howard University
Washington, DC (November2002)
• “Small Worlds on the Semantic Web”
Science on the Semantic Web (SWS) Workshop
Boston, Massachusetts (October 2002)
• “Evolving Strategies for the Prisoners Dilemma”
13th International Conference on Game Theory
Stony Brook, New York (July 2002)
• “Semantic Web Do-It-Yourself: Tools for Generating RDF Content”
NASA Goddard Semantic Web Interest Group
Greenbelt, Maryland (April 2002)
2.K.ii
Internal Talks
• “Video Chat for Pets”
HCIL Symposium
College Park, Maryland (May 22, 2012)
• “Social Network Strategies for Surviving the Zombie Apocalypse”
HCIL Symposium
College Park, Maryland (May 22, 2012)
• “The Twitter Mute Button”
HCIL Symposium
College Park, Maryland (May 22, 2012)
• “Understanding Users and Relationships in Social Networks”
MURI Virtual Brown Bag
College Park, Maryland (April 9, 2012)
• “Computing Trust in Social Networks”
Guest Lecture to PSY228Q: The psychology of social networking and social computing
College Park, Maryland (April 2, 2012)
• “Social Computing 2”
Guest Lecture to CMSC434: Intro to HCI
College Park, Maryland (November 30, 2011)
• “Social Computing 1”
Guest Lecture to CMSC434: Intro to HCI
College Park, Maryland (September 21, 2011)
• “Understanding Users and Relationships in Social Networks”
20
•
•
•
•
•
•
•
•
•
HCIL Symposium
College Park, Maryland (May 25, 2011)
“Trust, Ties, and Information Diffusion in Social Networks”
Guest Lecture in INFM289j: Social Media Campaigns for the WellBeing of Humankind
College Park, Maryland (November 22, 2010)
“Recommender Systems, Social Networks, and Applications”
Guest lecture to CPSP218J: Media, Self, and Society
College Park, Maryland (September 20, 2010)
“Twitter Use by the US Congress”
HCIL Symposium
College Park, Maryland (May 26, 2010)
“Recommender Systems, Social Networks, and Applications”
Guest lecture to CPSP218J: Media, Self, and Society
College Park, Maryland (September 8, 2009)
“Designing Systems to Help Find Experts”
iSchool Colloquium
College Park, Maryland (September 15, 2008)
“Social Networks on the Web: Challenges and Opportunities”
Smith School of Business, University of Maryland
College Park, Maryland (March 14, 2008)
“Social Trust for Information Access”
Center for Information Policy and E-Government (CIPEG) Policy Seminar Series
College Park, Maryland (February 25, 2008)
“Social information access -using social networks to sort, filter, and aggregate”
Human-Computer Interaction Lab (HCIL) Brown Bag Lunch
College Park, Maryland (November 8, 2008)
“Inferring Trust in Social Networks for Information Presentation”
Computational Linguistics and Information Processing (CLIP) Lab Colloquium
College Park, Maryland (October 3, 2007)
2.K.iii
Panels4
• Panelist, Social Media, NewsVision (digital media conference), March 30, 2009, Washington,
DC (invited)
• Panelist, Data Fusion and Data Enrichment Panel, Director of National Intelligence Open
Source Conference, July 2007, Washington, DC (invited)
2.K.iv
Media Mentions
Online and Print Media5
• Huffington Post: The Fall of Facebook - and What’s Next (June 25, 2014)
• Understanding User Generated Tags for Digital Collections: An Interview with Jennifer Golbeck* (May 1, 2013)
• Associated Press: What you ‘like’ on Facebook can be revealing (March 11, 2013)†
• Politico: ‘Weinergate’ a cautionary tale? (May 31, 2011)†
• Daily Caller: Facebook can serve as personality test (May 23, 2011)
4
5
Appearances on panels, not accompanied by papers. Refereed or invited as noted.
†Denotes cases where I was interviewed.
21
• ABC News: Facebook can serve as personality test (May 13, 2011)
• Jezebel: Your Facebook Is The New “Personality Test” (May 13, 2011)
• Time: Put Your Best Face Forward: Facebook Deemed an Accurate Personality Test for
Employers (May 10, 2011)
• ABC Online: Facebook can serve as personality test (May 9, 2011)
• Discovery News: Facebook can serve as personality test (May 9, 2011)
• Seattle Post Intelligencer: What Facebook tells your boss about your personality (May 9,
2011)
• Hindustan Times: Facebooks employee personality test (May 10, 2011)
• New Scientist: Why Facebook friends are worth keeping (July 15, 2010)†
• Corp Comms Magazine: Politicians Tweet Sweet Nothings (September 22, 2009)
• Sacramento Bee: Tweet-tweet goes Schwarzenegger, a big Twitter user (September 22, 2009)†
• Stars & Stripes (U.S. Military Newspaper)
– Japan Edition (September 22, 2009)†
– Mideast Edition (September 22, 2009)†
– Korea Edition (September 21, 2009)†
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
USTINET News: Study: Congress Tweets Lack Citizen Talk (September 21, 2009)
United Press International: Study: Congress Tweets lack citizen talk (September 21, 2009)†
Baltimore Sun: Congressional Twitter mostly twaddle (September 21, 2009)†
San Diego Union-Tribune: Politicians on Twitter have a lot to say about themselves (September 20, 2009)†
Lawrence Journal World & News: Members of Congress tweet their own horns (September
20, 2009)†
The Telegraph (Calcutta, India): Blowing tweet horns (September 20, 2009)†
The News Journal (Wilmington, DE): For Twitter-happy politicians, the service is all about
them (September 20, 2009)†
Honolulu Advertiser: Politicians Tweets self-promotional (September 20, 2009)†
Huffington Post: Politicians On Twitter: Tweets By Lawmakers Boastful Or Boring: Study
(September 19, 2009)†
Hawaii Reporter: Politicians Tweets Are Mostly Self-Promotional, Researchers Say (September 19, 2009)†
Austin American Statesman: Lawmakers use Twitter for self-promotion, study finds (September 19, 2009)†
The Arizona Republic: Surprise! Twitter from D.C. about self-promotion (September 18,
2009)†
St. Petersburg Times: Times Wires (September 18, 2009)†
The Hill: Lawmakers Tweets Largely Self-Promotional (September 18, 2009)†
The Washington Post: Politicians Tweets Are Mostly Self-Promotional, Researchers Say
(September 18, 2009)†
Politico: Study: Congress Needs Twitter Help (September 16, 2009)†
Kansas City Star: Study: Congress all a Twitter (September 15, 2009)†
Ars Technica: Who do you trust 2.0: Building better preference predictions (September 21,
2008)†
Delmarva Daily Times: ALL ABOUT ME: ‘25 Things’ becomes one of Facebook‘s biggest
fads. (February 27, 2008)†
WEYI NBC25: Facebook backs down on change (February 18, 2009)†
Wired.com: Obama Supporters Act to Clear FUD. (November 12, 2007)†
22
• Physics World: Talking Physics in the Social Web (January 2007)
• Salon.com: You are who you know (June 15, 2004)†
Podcasts, Radio, and TV
• , NPR, The Kojo Nnamdi Show, guest host (January 2014-present)
• NPR, To The Point (January 3, 2014)
• NPR, The Kojo Nnamdi Show, interview on “From :) to GIFS: Expressing ourselves with
images online” (March 21, 2013)
• Wisconsin Public Radio, The Joy Cardin Show, interview on “What your Facebook Likes say
about you” (March 21, 2013)
• NPR, interview on social media and the Olympics (August 1, 2012)
• NPR, The Kojo Nnamdi Show, interview on “The Future Of Neighborhood Communication”
(July 31, 2012)
• NPR, The Kojo Nnamdi Show, interview on “Frictionless Web: Social Readers And Seamless
Sharing” (June 12, 2012)
• NPR, The Kojo Nnamdi Show, interview on “The Interest in Pinterest” (February 28, 2012)
• NPR, The Kojo Nnamdi Show, interview on “The New Sharing Economy” (October 31, 2011)
• NPR, The Kojo Nnamdi Show, interview on “Social Networking Grows Up” (March 24, 2011)
• NPR, The Kojo Nnamdi Show, interview on photos and social media (February 15, 2011)
• NPR, The Animal House, interview on social networks for pets (January 15, 2011)
• BBC World Service Newshour, interview on Twitter use by PMs (October 21, 2009)
• WHIO TV, interview on the use of Twitter by Congress (October 3, 2009)
• KCSN Radio, interview on the use of Twitter by Congress (September 21, 2009)
• WTOP Radio, interview on the use of Twitter by Congress (September 15, 2009)
• NBC 4, TV interview on Facebook data sharing policy (February 17, 2009)
• Science Podcast, interview on trust in social networks (September 18, 2008)
• NBC 4, TV interview on internet predators (February 21, 2008)
• The Diane Rehm Show (National Public Radio), panelist for discussion of Social Networks
(July 10, 2006)
3
Teaching, Mentoring, and Advising
3.A
Courses Taught in the Last Five Years
• INST 775: HCI Capstone Prep
– Fall 2013 (enrollment 12)
• INST 631 / LBSC795: Fundamentals of HCI
– Fall 2012 (enrollment 13)
– Fall 2011 (enrollment 15)
• INST 633 / LBSC708L: Analyzing Social Networks and Social Media
–
–
–
–
–
Spring 2011 (enrollment 22)
Spring 2013 (enrollment 18)
Summer 2013 (enrollment 19)
Winter 2013 (enrollment 13)
Summer 2015 enrollment 20
23
• INFM289I: Social Networks: Technology and Society
– Spring 2010 (enrollment 67)
– Fall 2010 (enrollment 64)
– Spring 2012 (enrollment 75)
• LBSC 690: Information Technology
–
–
–
–
–
–
Summer 2012 (enrollment 18)
Spring 2012 (enrollment 18)
Winter 2011 (enrollment 22)
Winter 2010 (enrollment 16)
Spring 2009 (enrollment 26)
Fall 2007 (enrollment 25)
• LBSC 743: Development of Internet Applications
– Spring 2010 (enrollment 32)
– Fall 2009 (enrollment 27)
– Spring 2009 (enrollment 36)
• LBSC 888: Doctoral Seminar
– Fall 2008 (enrollment 7)
– Spring 2014 (enrollment 7)
• INFM 220: Information Users in Social Context
– Spring 2008 (enrollment 22)
• CMSC 498N: Small Worlds, Social Networks, and Web Algorithms
– Spring 2007 (enrollment 14)
3.B
Course or Curriculum Development
• Fall 2012: Development of HCI Masters capstone classes, INST 775 and 776
• Fall 2011: Redevelopment of LBSC795 / INST631 for HCI Masters program
• Spring 2010: First offering of new course for undergraduate iSeries, INFM289I: Social Networks, Technology, and Society
• Winter 2010. Developed online version of LBSC690: Information Technology
• Spring 2009. First offering of new course. INFM 743: Development of Internet Applications
• Spring 2009. Significant course revision. LBSC 690: Information Technology
• Spring 2008. First offering of new course. INFM 220: Information Users in Social Context
• Fall 2007. Development of new course LBSC 888: Doctoral Seminar (with Allison Druin)
• Spring 2007. First offering of new course. CMSC 498N: Small Worlds, Social Networks, and
Web Algorithms
3.C
3.C.i
Textbooks, Manuals, Notes, Software, Web pages and Other Contributions
to Teaching
Textbooks
• Jennifer Golbeck, Social Network and Social Media Analysis. Burlington, MA: Morgan
Kaufmann, 2013.
24
3.C.ii
Other Contributions to Teaching
• Developed Web-accessible course material (slides, exercises, assignments, sample exams, etc.)
for LBSC 690. Adapted from material by Jimmy Lin and Allison Druin.
• Developed Web-accessible course material for INFM 743.
• Developed Web-accessible course material for INFM 220.
• Built three two-week modules (mini-courses) for LBSC 888.
• Developed and implemented online module system for LBSC 888, where faculty can build
and submit two-week modules for the doctoral seminar.
• Developed Web-accessible course material for CMSC 498N.
3.E
3.E.i
Advising: Other Than Research Direction
Undergraduate
• Anthony Rogers, Individual Studies Program, Fall 2007 – present
• Ben Falk, Individual Studies Program, Spring 2008 – present
• Ryan McCormick, Individual Studies Program, Spring 2008 – present
3.E.ii
Master’s
• Spring 2009: 13 advisees
• Fall 2008: 13 advisees
3.F
3.F.i
Advising: Research Direction
Undergraduate
• Danny Laurence
Spring 2012 – present
Research topic: Computing trust in social networks
• Elaine Wang
Spring 2012 – present
Research topic: Multilingual Use of Twitter
• Vincent Kuyatt (Undergraduate Student, Computer Science)
Spring 2011
Research Topic: Real time strategy games for social strategy analysis
• Michon Edmonson (Undergraduate Student, Computer Science)
Spring 2011 – present
Research Topic: Computing personality and trust
• Wendy Mock (Undergraduate Student, Computer Science)
Spring 2011 – present
Research Topic: Social tagging of images
• Eric Norris (Undergraduate Student, Computer Science)
Summer 2010 – present
Research Topic: processing social network data
25
• Nima Rad (Undergraduate Student, Computer Science)
Summer 2010 – Winter 2011
Research Topic: Games for understanding social strategies
• Karen Turner (Undergraduate Student, Psychology)
Spring 2010 – Fall 2010
Research topic: Use of Facebook
• Anthony Rogers (Undergraduate Student, Individual Studies)
Spring 2008 – present
Research topic: Social networks on the web
• Stuart Moore (Undergraduate Student)
Spring 2008, In the context of INFM 220
Research topic: Expert search
• Joanne Kim (Undergraduate Student)
Spring 2008, In the context of INFM 220
Research topic: Expert search
• Mariya Filippova (Undergraduate Student, Computer Science)
Fall 2007 – Spring 2008
Research topic: Social Applications in Facebook
• Greg Phillips (Undergraduate Student, Computer Science)
Spring 2008, In the context of INFM 220
Research topic: Sentiment analysis in online communities
• Matthew Rothstein (Undergraduate Student, Computer Science)
Spring 2007 – Summer 2008
Research topic: Merging social networks on the Semantic Web with FOAF
• Michael Wasser (Undergraduate Student, Computer Science)
Fall 2005 – Spring 2007
Research topic: Adding social context to web pages
3.F.ii
Master’s
Masters Thesis Committees
• Member, Thesis Committee
Kelly Hoffman (MLS student, the iSchool): Fall 2007 – Spring 2008
• Member, Thesis Committee
Chris Zamerelli (MLS student, the iSchool): Fall 2007 – Spring 2008
• Member, Thesis Committee
D. Adam Anderson (MLS student, the iSchool): Fall 2007 – Spring 2008
26
Other
• Zahra Ashktorab (HCIM Student, the iSchool)
Fall 2011 – present
Research topic; Social Recommender Systems
• Beth Emmerling (PhD student, the iSchool)
Spring 2010 – Fall 2011
Research topic: Image tagging
• Cristina Robles (MLS student, the iSchool)
Spring 2010 – Spring 2011
Research topic: Use of Facebook
• Alon Motro (MIM student, the iSchool)
Spring 2009 – Spring 2012
Research topic: Computing trust in social networks
• Jeanne Kramer-Smyth (MLS student, the iSchool)
Fall 2008 – Spring 2009
In the context of NEH Digital Humanities Startup Grant
Research Topic: Development of ArchivesZ visualization tool for archival collections
• Rishabh Vyas (MIM student, the iSchool)
Fall 2008 – Spring 2009
In the context of a Graduate Research Assistantship (GRA)
Research Topic: expert search through document indexing
• Manasee Mahajan (MIM student, the iSchool)
Fall 2007 – Fall 2008
Research Topic: expert search through document indexing
3.F.iii
Doctoral
As Advisor/Co-Advisor
•
•
•
•
•
•
Advisor, Zahra Ashktorab (Ph.D. Student, iSchool)
Advisor, Cody Buntain (Ph.D. Student, Computer Science)
Advisor, Irene Eleta (Ph.D. Student, iSchool)
Advisor, Jes Koepfler (Ph.D. Student, iSchool)
Advisor, John Kleint (Ph.D. Student, Computer Science)
Co-Advisor with Don Perlis, Hamid Shahri (Ph.D Student, Computer Science)
Graduated Spring 2011
First permanent position: Technology Researcher at the Mayo Clinic
• Co-Advisor with Jim Hendler, Vladimir Kolovski (Ph.D. Student, Computer Science)
Graduated May 2008.
First permanent position: Research Scientist, Oracle (Nashua, NH)
• Co-Advisor with Jim Hendler, Christian Halaschek-Weiner (Ph.D. Student, Computer Science)
Graduated December 2007.
First permanent position: Chief Technology Officer of Clados Management LLC.
27
Other Dissertation Committees
• Member, dissertation committee
Ed Condon (Ph.D. Student, Computer Engineering), Fall 2012–present
• Member, dissertation committee
Jared Sylvester (Ph.D. Student, Computer Science, Fall 2014
• Member, dissertation committee
Megan Monroe (Ph.D. Student, Computer Science), Fall 2013–Spring 2014
• Member, dissertation committee
Kan Leung Cheng (Ph.D. Student, Computer Science), Fall 2010–Summer 2013
• Member, dissertation committee
Greg Walsh (Ph.D. Student, the iSchool), Fall 2010–Summer 2012
• Member, dissertation committee
Bo Han (Ph.D. Student, Computer Science), Summer 2012
• Member, dissertation committee
Tom Dubois (Ph.D. Student, Computer Science), Fall 2010 – Spring 2011
• Member, dissertation committee
Elena Zheleva (Ph.D. Student, Computer Science), Fall 2008 – Spring 2011
• Member, dissertation committee
Hamid Shahri (Ph.D. Student, Computer Science): Fall 2009 – Spring 2011
• Member, dissertation committee
Chuk-Yang Seng (Ph.D. Student, Computer Science): Fall 2008 – Summer 2009
• Member, dissertation committee
Adam Perer (Ph.D. Student, Computer Science): Fall 2007 – Spring 2008
Other6
• Dana Rotman (Ph.D. Student, the iSchool): Fall 2009 – present
Research Topic: Community structure in YouTube
• Tom DuBois (Ph.D. student, Computer Science): Spring 2009 – Spring 2011
Research Topic: Computing trust in social networks
• Justin Grimes (Ph.D. Student, the iSchool): Spring 2009
Research Topic: Twitter Usage in Congress
• Elena Zheleva (Ph.D. Student, Computer Science): Fall 2008 – Spring 2011
Research Topic: Link prediction in social networks
• Christina Pikas (Ph.D. Student, the iSchool): Spring 2008
Research Topic: Social networks in science blogs
• Philip Fei Wu (Ph.D. Student, the iSchool), Fall 2007 – Spring 2008
Research Topic: Community Response Grids
6
Students with whom I have had significant research interaction on specific projects, in a capacity other than
their advisor/co-advisor.
28
4
Service
4.A
4.A.i
Professional
Offices and committee memberships held in professional organizations7
• World Wide Web Consortium Semantic Web Best Practices Working Group, March 2004 –
October 2004
4.A.ii
Reviewing activities for agencies
• Review panelist, NASA Postdoctoral Fellows program Summer 2011
• Review panelist, National Science Foundation (NSF), Directorate for Computer and
mation Science and Engineering (CISE), Spring 2011
• Review panelist, National Science Foundation (NSF), Directorate for Computer and
mation Science and Engineering (CISE), Spring 2010
• Review panelist, National Science Foundation (NSF), Directorate for Computer and
mation Science and Engineering (CISE), Fall 2009
• Review panelist, National Science Foundation (NSF), Directorate for Computer and
mation Science and Engineering (CISE), Fall 2008
• Outside Reviewer, National Science Foundation (NSF), Directorate for Computer and
mation Science and Engineering (CISE), Fall 2007
4.A.iii
InforInforInforInforInfor-
Other unpaid services to local, state, and federal agencies
• Production of video campaign and social media contest for Department of Defense anti-obesity
initiative, in conjunction with Deputy Assistant Secretary of Defense for Health Affairs
Summer 2012 – present
4.B
Campus
4.B.i
College8
•
•
•
•
•
•
•
•
•
•
•
•
Program Director, HCI Masters Program, Summer 2012 – present)
Director, Human-Computer Interaction Lab (Spring 2011 – present)
Member, HCI Masters Committee (Fall 2009 – Spring 2012)
Member, iSchool Search Committee (Fall 2011– Spring 2012)
Chair, iSchool Student Awards Committee (Fall 2011 – Spring 2012)
Co-Director, HCIL (Spring 2009 – Spring 2011)
Chair, iSchool Undergraduate Committee (Fall 2010 – Spring 2011)
Member, iSchool Search Committee (Fall 2010 – Spring 2011)
Member, iSchool Search Committee (Fall 2009 – Spring 2011)
Member, iSchool ad hoc Research Committee (Fall 2009 – Spring 2011)
Member, iSchool Undergraduate Committee (Fall 2008 – Spring 2009)
Assistant Director, Center for Information Policy and E-Government (Fall 2007 – Spring
2010)
• Member, iSchool Doctoral Committee (Fall 2007 – Spring 2010)
7
Position on journal board, chairship/membership on conference program committees, and related reviewing
activities already reported in Section 2.K are not repeated here.
8
Membership on dissertation/examination committees are listed in Section 3.F.iii and not duplicated here.
29
• Secretary, College Assembly (Fall 2008 – Spring 2009)
4.C
University
• Member, University of Maryland Provost Search Committee (Fall 2011 – Spring 2012)
30
EXHIBIT B
Exhibit B: List of Materials Relied On
I relied on the following documents and materials in forming my opinions:
Documents from Campbell, et al. v. Facebook, Inc.:
Supplemental Responses and Objections to Plaintiffs’ First Set of Interrogatories
Facebook’s Second Supplemental Responses and Objections to Plaintiffs’ Narrowed
Second Set of Interrogatories
Deposition of Ray He (September 25, 2015)
Deposition of Michael Adkins (October 28, 2015)
Plaintiffs’ Consolidated Amended Complaint
Exhibit F to the Declaration of Alex Himel on Behalf of Defendant Facebook, Inc.
FB000011543
FB000002651
FB000003118
FB000002651
FB000002843
FB000007286
FB000006178
FB000010688
FB000008505
FB000010688
FB000008722
FB000000298
FB000008643
FB000008499
FB000002141
FB000002190
FB000002196
FB000006429
FB000000699
FB000002197
FB000001599
FB000001608-9
FB000000425
FB000005827
FB000005802-R
FB000008499
Source Code Produced by Facebook
Other Materials
https://web.archive.org/web/20101016010319/http://developer.yahoo.com/blogs/ydn/post
s/2010/10/how-many-users-have-javascript-disabled/
https://gds.blog.gov.uk/2013/10/21/how-many-people-are-missing-out-on-javascriptenhancement/
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Campbell v. Facebook Inc., 77 F. Supp. 3d 836, 844 (N.D. Cal. 2014).
In re Google Inc. Gmail Litig., 2013 U.S. Dist. LEXIS 172784 (N.D. Cal. Sept. 26, 2013)
In re Carrier IQ, Inc., Consumer Privacy Litig., 78 F. Supp. 3d 1051, 1076 (N.D. Cal.
2015)
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