Data-driven User Behavioral Modelling and Mining from Social Media

Workshop at the CIKM 2013 (
Oct 28, 2013  -  San Francisco, CA.

Important Dates

 Submission Deadline:     July 26, 2013   
 Author Notification:         August 12, 2013
 Camera-Ready version:   August 19, 2013

 Workshop:                     October 28, 2013


The massive amount of data being generated on social media sites, such as Twitter and Facebook, can be used to better understand people and predict their behavior. In this workshop, rather than continuing down the path of aggregating data across many users, we focus on the creation of deep models of individual users. In recent years, this has been active area of research and various analytic techniques have been applied to infer properties of users, including home location, gender, age, regional origin, ethnicity, political orientation, expertise, location preferences, enterprise preferences, and personality. Our workshop aims to bring together researchers and practitioners from diverse areas, such as user modeling, social media analysis, natural language processing, data mining, machine learning, privacy and security, to: 1) discuss the many remaining technical challenges, 2) the challenges of balancing expression with the need for privacy, and 3) develop an agenda for future research in this area. 


Jalal Mahmud, IBM Research – Almaden, USA
James Caverlee, Texas A&M University, USA   
Jeffrey Nichols, IBM Research – Almaden, USA
John O' Donovan, University of California, Santa Barbara, USA  
Michelle Zhou, IBM Research Almaden, USA