Social media news communities: Gatekeeping, coverage, and statement bias

Diego Saez-Trumper, Carlos Castillo, Mounia Lalmas

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

38 Citations (Scopus)

Abstract

We examine biases in online news sources and social media communities around them. To that end, we introduce unsupervised methods considering three types of biases: selection or "gatekeeping" bias, coverage bias, and statement bias, characterizing each one through a series of metrics. Our results, obtained by analyzing 80 international news sources during a two-week period, show that biases are subtle but observable, and follow geographical boundaries more closely than political ones. We also demonstrate how these biases are to some extent amplified by social media. Copyright is held by the owner/author(s).

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages1679-1684
Number of pages6
DOIs
Publication statusPublished - 11 Dec 2013
Event22nd ACM International Conference on Information and Knowledge Management, CIKM 2013 - San Francisco, CA, United States
Duration: 27 Oct 20131 Nov 2013

Other

Other22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
CountryUnited States
CitySan Francisco, CA
Period27/10/131/11/13

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Keywords

  • Framing
  • News bias
  • Online news

ASJC Scopus subject areas

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

Cite this

Saez-Trumper, D., Castillo, C., & Lalmas, M. (2013). Social media news communities: Gatekeeping, coverage, and statement bias. In International Conference on Information and Knowledge Management, Proceedings (pp. 1679-1684) https://doi.org/10.1145/2505515.2505623