Context over time: Modeling context evolution in social media

Md Hijbul Alam, Woo Jong Ryu, Sang-Geun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The rise of online social media has led to an explosion in user-generated content. However, user-generated content is difficult to analyze in isolation from its context. Accordingly, context detection and tracking its evolution is essential to understanding social media. This paper presents a statistical model that can detect interpretable topics along with their contexts. A topic is represented by a cluster of words that frequently occur together, and a context is represented by a cluster of hashtags that frequently occur with a topic. The model combines a context with a related topic by jointly modeling words with hashtags and time. Experiments on real datasets demonstrate that the proposed model successfully discovers both meaningful topics and contexts, and tracks their evolution.

Original languageEnglish
Title of host publicationDUBMOD 2014 - Proceedings of the 3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, co-located with CIKM 2014
PublisherAssociation for Computing Machinery
Pages15-18
Number of pages4
Volume2014-November
EditionNovember
DOIs
Publication statusPublished - 2014 Nov 3
Event3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, DUBMOD 2014, Co-located with 23rd ACM Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China
Duration: 2014 Nov 3 → …

Other

Other3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, DUBMOD 2014, Co-located with 23rd ACM Conference on Information and Knowledge Management, CIKM 2014
CountryChina
CityShanghai
Period14/11/3 → …

Keywords

  • Context and topic evolution
  • Social media
  • Topic model

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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  • Cite this

    Alam, M. H., Ryu, W. J., & Lee, S-G. (2014). Context over time: Modeling context evolution in social media. In DUBMOD 2014 - Proceedings of the 3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, co-located with CIKM 2014 (November ed., Vol. 2014-November, pp. 15-18). Association for Computing Machinery. https://doi.org/10.1145/2665994.2665996