ACL Joint Workshop on
Social Dynamics and Personal Attributes in Social Media

June 27, 2014

Baltimore, MD, USA

Workshop Schedule

8:40 - 8:50 Welcome notes

8:50 - 9:50 Invited talk by Derek Ruths "The Promises and Pitfalls of Demographic Inference in Social Media"

9:50 - 10:45 Oral Session 1:

  • 9:50 - 10:05 Linguistic Style-Shifting in Online Social Media
    Umashanthi Pavalanathan and Jacob Eisenstein
  • 10:05 - 10:25 Detecting sociostructural beliefs about group status differences in online discussions
    Brian Riordan, Heather Wade and Afzal Upal
  • 10:25 - 10:45 Using county demographics to infer attributes of Twitter users
    Ehsan Mohammady and Aron Culotta

10:45 - 10:55 Coffee break

10:55 - 11:30 Oral Session 2:

  • 10:55 - 11:10 The Enrollment Effect: A Study of Amazon's Vine Program
    Dinesh Puranam and Claire Cardie
  • 11:10 - 11:30 Discourse Analysis of User Forums in an Online Weight Loss Application
    Lydia Manikonda, Heather Pon-Barry, Subbarao Kambhampati, Eric Hekler and David W. McDonald

11:30 - 12:30 Panel (Hanna Wallach, Jacob Eisenstein, Cristian Danescu-Niculescu-Mizil and Jimmy Lin)

12:30 - 1:30 Lunch Break

1:30 - 2:25 Oral Session 3:

  • 1:30 - 1:50 A Unified Topic-Style Model for Online Discussions
    Ying Ding, Jing Jiang and Qiming Diao
  • 1:50 - 2:10 Self-disclosure topic model for Twitter conversations
    JinYeong Bak, Chin-Yew Lin and Alice Oh
  • 2:10 - 2:25 Detecting and Evaluating Local Text Reuse in Social Networks
    Shaobin Xu, David Smith, Abby Mullen and Ryan Cordell

2:25 - 2:35 Coffee break

2:35 - 3:35 Invited talk by Mark Dredze "Opportunities from Social Media Data for Public Health"

3:35 - 3:45 Coffee Break

3:45 - 4:30 Oral Session 4:

  • 3:45 - 4:00 Generating Subjective Responses to Opinionated Articles in Social Media: An Agenda-Driven Architecture and a Turing-Like Test
    Tomer Cagan, Stefan L. Frank and Reut Tsarfaty
  • 4:00 - 4:15 A Semi-Automated Method of Network Text Analysis Applied to 150 Original Screenplays
    Starling Hunter
  • 4:15 - 4:30 Measuring Constructiveness in Ranking Tasks
    Vlad Niculae, Cristian Danescu-Niculescu-Mizil, Natalya N. Bazarova and Y. Connie Yuan

4:30 - 5:30 Poster Session

5:30 - 5:40 Closing Remarks


The list of accepted papers (oral talks and posters) is available here.

The Workshop on Latent Attribute Prediction in Social Media and the Workshop on NLP and Social Dynamics have merged!




NLP and Social Dynamics Aspect: Language is a set of publicly agreed conventions that serves the purpose of inter-personal communication. Speakers (or writers) try to convey a message, instill an idea or make an impression on the listeners. Listeners (or readers), in turn, are affected by the message and may respond to it. Language, in that sense, is an important vehicle that shapes (and is shaped by) social dynamics.

Traditional NLP research, however, focuses on "documents" (either of full length or on the sentence level), rather than on the communication process as reflected by language use. Common examples of traditional NLP research are parsing, document classification, machine translation, and sentiment analysis at the sentence and document level without considering the social dynamics of the people who are writing and reading those texts.

We propose to move beyond analyzing the informational aspect of documents and discuss ways in which NLP can contribute to gaining insights about the interplay between language use and various levels of social dynamics.

Personal Analytics in Social Media Aspect: There are many important social science questions and commercial applications that are impacted by the large amounts of diverse personalized data emerging from social media. These data can reveal user interests, preferences and opinions, as well as trends and activity patterns for companies and their products.

The automatic prediction of latent attributes from discourse in social media includes topics such as:
  • inferring user/customer demographic profiles (gender, age, religion, social status, race, ethnicity, origin),
  • predicting user interests (sports, movies) and preferences (political favorites or product likes),
  • classifying sentiment, personality, emotional states (onset of depression), and opinions held by an author,
  • analyzing general trends and influence for companies and products.

Important Dates

All deadlines are calculated at 11:59pm (PST/GMT -7 hours)
28 March 2014: Workshop Paper Due Date
14 April 2014: Notification of Acceptance
28 April 2014: Camera-ready papers due
27 June 2014: Workshop Date

Call for Papers

We invite original and unpublished research papers on all topics related to text-driven latent attribute prediction in social media, including but not limited to the topics listed below:

NLP and Social Dynamics:

  • Emergence and diffusion of slang, neologisms and metaphors
  • Emotion dynamics in social media conversation threads
  • Evolution of word formation and word meaning
  • Language coordination and lexical entrainment
  • Language evolution through history and language variation across communities
  • Linguistic (phonological, morphological, etc) factors in word formation
  • Linguistic and social factors in acceptance of new words and phrases
  • Linguistic factors in information diffusion and information cascades.
  • NLP techniques for analyzing social media
  • Persuasive language and (online) campaigns
  • Pragmatics of language
  • Social dynamics in (blog/news story) comment threads
  • Social relationships and language use
  • Sociolinguistic perspective of social media language use

Personal Analytics:

  • dynamic and streaming nature of social media data;
  • joint latent attribute prediction (e.g., age together with political preference);
  • multi-relational aspect of social media data (e.g., networks of friends, followers, user mentions etc.);
  • generalization of the existing models for text-driven author attribute prediction;
  • scalability to other understudied languages and dialects in social media;
  • data collection, sharing and labeling biases for personal analytics in social media;
  • language variations in social media for the users with different attributes (e.g. gender, age and native language);
  • mood, sentiment, emotion and opinion analysis of authors in social media;
  • emotional states, distress, mental condition classification from communications in social networks;
  • community and network structure analysis for latent attribute prediction;
  • security, identity and privacy issues for personal analytics in social media.
Papers should follow the ACL long paper format (up to 9 pages of content plus two extra pages for references) or short paper format (5 pages plus 2 pages for references) as described here and have to be submitted via this link.

Workshop Organizers

Program Committee

  • Abigail Jacobs (University of Colorado at Boulder, USA)
  • Alan Ritter (Carnegie Mellon University, USA)
  • Alejandro Jaimes (Yahoo Research, Barcelona)
  • Alessandro Moschitti (QCRI, Qatar)
  • Ancsa Hannak (Northeastern University, USA)
  • Ari Rappaport (The Hebrew University, Israel)
  • Aron Culotta (Illinois Institute of Technology, USA)
  • Brendan O'Connor (Carnegie Mellon University, USA)
  • Brian Keegan (Northeastern University, USA)
  • Carlo Strapparava (FBK)
  • Chin-Yew Lin (Microsoft Research Asia)
  • Chris Dyer (Carnegie Mellon University, USA)
  • Cristian Danescu-Niculescu-Mizil (Max Planck Institute SWS)
  • Dan Jurafsky (Stanford University, USA)
  • Daniel Romero (University of Michigan, USA)
  • David Smith (Northeastern University, USA)
  • Delip Rao (Amazon, USA)
  • Derek Ruths (McGill University, Canada)
  • Dong Nguyen (University of Twente, Netherlands)
  • Eugene Kharitonov (Yandex, Russia)
  • Francisco Iacobelli (Northeastern Illinois University, USA)
  • Gideon Dror (Yahoo! Research, USA)
  • Glen Coppersmith (Johns Hopkins University, USA)
  • Haewoon Kwak (Telefonica)
  • Idan Szpektor (Yahoo! Research, USA)
  • Ilia Chetviorkin (Lomonosov Moscow State University, Russia)
  • Ingmar Weber (QCRI, Qatar)
  • Jacob Eisenstein (Georgia Institute of Technology, USA)
  • James Caverlee (Texas A&M University, USA)
  • John Henderson (MITRE, USA)
  • Margaret Mitchell (Microsoft Research, USA)
  • Mark Dredze (Johns Hopkins University, USA)
  • Michael Gamon (Microsoft Research, USA)
  • Michael Paul (Johns Hopkins University, USA)
  • Omri Abend (University of Edinburgh, UK)
  • Patrick Pantel (Microsoft Research, USA)
  • Paul Cook (University of Melbourne)
  • Pavel Braslavski (KonturLabs, Russia)
  • Pavel Sergyukov (Yandex, Russia)
  • Philip Resnik (University of Maryland, USA)
  • Rebecca Knowles (Johns Hopkins University, USA)
  • Reut Tzarfati (Weizman Institute of Science, Israel)
  • Rivka Levitan (Columbia University, USA)
  • Roi Reichart (Israel Institute of Technology)
  • Roy Schwartz (The Hebrew University)
  • Saif Mohammad (National Research Council, Canada)
  • Silviu-Petru Cucerzan (Microsoft Research, USA)
  • Souneil Park (University of Michigan)
  • Vasileios Lampos (University College London, UK)
  • Vivi Nastase (FBK, Italy)
  • Yael Netzer (Ben Gurion University, Israel)
  • Yoav Goldberg (Bar Ilan University, Israel)
  • Yu-Ru Lin (University of Pittsburgh, USA)
  • Yuval Pinter (Yahoo! Research)