Dynamic user-level affect analysis in social media: Modeling violence in the dark web

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

2 Scopus citations

Abstract

Affect represents a person's emotions toward objects, issues or other persons. Recent years have witnessed a surge in studies of users' affect in social media, as marketing literature has shown that users' affect influences decision making. The current literature in this area, however, has largely focused on the message level, using text-based features and various classification approaches. Such analyses not only overlook valuable information about the user who posts the messages, but also fail to consider that users' affect may change over time. To overcome these limitations, we propose a new research design for social media affect analysis by specifically incorporating users' characteristics and the time dimension. We illustrate our research design by applying it to a major Dark Web forum of international Jihadists. Empirical results show that our research design allows us to draw on theories from other disciplines, such as social psychology, to provide useful insights on the dynamic change of users' affect in social media.

Original languageEnglish (US)
Title of host publicationProceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Pages1-6
Number of pages6
DOIs
StatePublished - Sep 22 2011
Event2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 - Beijing, China
Duration: Jul 10 2011Jul 12 2011

Publication series

NameProceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011

Other

Other2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
CountryChina
CityBeijing
Period7/10/117/12/11

Keywords

  • Affect analysis
  • Persuasion
  • Social media
  • Social network analysis
  • Time dimension

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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    Zeng, S., Lin, M., & Chen, H. (2011). Dynamic user-level affect analysis in social media: Modeling violence in the dark web. In Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 (pp. 1-6). [5984041] (Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011). https://doi.org/10.1109/ISI.2011.5984041