Predicting ideological friends and foes in twitter conflicts

Zhe Liu, Ingmar Weber

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

7 Citations (Scopus)

Abstract

The rise in popularity of Twitter in recent years has in parallel led to an increase in online controversies. To monitor and control such conflicts early on, we design and evaluate a language-agnostic classifier to tell pairs of ideological friends from foes. We build the classifier using features from four different aspects: user-based, interaction-based, relationship-based and conflict-based. By experimenting with three large data sets containing diverse conflicts, we demonstrate the effectiveness of language-agnostic classification of ideological relation, achieving satisfactory results across all three data sets. Such a classifier potentially enables studies of diverse conflicts on Twitter on a large scale.

Original languageEnglish
Title of host publicationWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages575-576
Number of pages2
ISBN (Electronic)9781450327459
DOIs
Publication statusPublished - 7 Apr 2014
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: 7 Apr 201411 Apr 2014

Other

Other23rd International Conference on World Wide Web, WWW 2014
CountryKorea, Republic of
CitySeoul
Period7/4/1411/4/14

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Keywords

  • Classification
  • Conflict
  • Political ideology
  • Social network
  • Twitter

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Liu, Z., & Weber, I. (2014). Predicting ideological friends and foes in twitter conflicts. In WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web (pp. 575-576). Association for Computing Machinery, Inc. https://doi.org/10.1145/2567948.2576964