LAPSM 2014 - ACL Workshop on Latent Attribute Prediction in Social Media

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)
21 March 2014: Workshop Paper Due Date
11 April 2014: Notification of Acceptance
28 April 2014: Camera-ready papers due (firm deadline)
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We invite original and unpublished research papers on all topics related to text-driven latent attribute prediction in social media, including but not limited to the topics listed below:
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 8 page paper format as described here and have to be submitted via this link.
Workshop Organizers
Svitlana Volkova (Johns Hopkins University, USA)
Benjamin Van Durme (Johns Hopkins University, USA)
David Yarowsky (Johns Hopkins University, USA)
Program Committee:
Abigail Jacobs (University of Colorado Boulder, USA)
Alessandro Moschitti (QCRI, Qatar)
Allan Ritter (Carnegie Melon University, USA)
Aron Culotta (Illinois Institute of Technology, USA)
Chris Dyer (Carnegie Melon University, USA)
Delip Rao (GlassDoor, USA)
Derek Ruth (McGill University, Canada)
Dong Nguyen University of Twente, Netherlands)
Eugene Kharitonov (Yandex, Russia)
Francisco Iacobelli (Northeastern Illinois University, USA)
Glen Coppersmith (Johns Hopkins University, USA)
Ilia Chetviorkin (Lomonosov Moscow State University, Russia)
Jacob Eisenstein (Georgia Institute of Technology, USA)
John Henderson (MITRE, USA)
Mark Dredze (Johns Hopkins University, USA)
Meg Mitchell (Microsoft Research, USA)
Michael Paul (Johns Hopkins University, USA)
Michael Gamon (Microsoft Research, USA)
Patrick Pantel (Microsoft Research, USA)
Pavel Braslavski (KonturLabs, Russia)
Pavel Sergyurkov (Yandex, Russia)
Philip Resnik (University of Maryland, USA)