DUBMOD ''13-International Workshop on Data-driven User Behavioral Modelling and Mining from Social Media Conference Paper uri icon

abstract

  • Massive amounts of data are being generated on social media sites, such as Twitter and Facebook. These data can be used to better understand people (e.g., personality traits, perceptions, and preferences) and predict their behavior. As a result, a deeper understanding of users and their behavior can benefit a wide range of intelligent applications, such as advertising, social recommender systems, and personalized knowledge management. These applications will also benefit individual users themselves and optimize their experience across a wide variety of domains, such as retail, healthcare, and education. Since mining and understanding user behavior from social media often requires interdisciplinary effort, including machine learning, text mining, human-computer interaction, and social science, our workshop aims to bring together researchers and practitioners from multiple fields to discuss the creation of deeper models of individual users by mining the content that they publish and the social networking behavior that they exhibit. Copyright is held by the author/owner(s).

name of conference

  • Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13

published proceedings

  • PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13)

author list (cited authors)

  • Mahmud, J., Nichols, J., Zhou, M., Caverlee, J., & O'Donovan, J.

citation count

  • 0

complete list of authors

  • Mahmud, Jalal||Nichols, Jeffrey||Zhou, Michelle||Caverlee, James||O'Donovan, John

editor list (cited editors)

  • He, Q. i., Iyengar, A., Nejdl, W., Pei, J., & Rastogi, R.

publication date

  • October 2013