#Snowden: Understanding biases introduced by behavioral differences of opinion groups on social media

Q. Vera Liao, Wai Tat Fu, Markus Strohmaier

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

Abstract

We present a study of 10-month Twitter discussions on the controversial topic of Edward Snowden. We demonstrate how behavioral differences of opinion groups can distort the presence of opinions on a social media platform. By studying the differences between a numerical minority (anti-Snowden) and a majority (pro-Snowden) group, we found that the minority group engaged in a "shared audiencing" practice with more persistent production of original tweets, focusing increasingly on inter-personal interactions with like-minded others. The majority group engaged in a "gatewatching" practice by disseminating information from the group, and over time shifted further from making original comments to retweeting others'. The findings show consistency with previous social science research on how social environment shapes majority and minority group behaviors. We also highlight that they can be further distorted by the collective use of social media design features such as the "retweet" button, by introducing the concept of "amplification" to measure how a design feature biases the voice of an opinion group. Our work presents a warning to not oversimplify analysis of social media data for inferring social opinions.

Original languageEnglish (US)
Title of host publicationCHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages3352-3363
Number of pages12
ISBN (Electronic)9781450333627
DOIs
StatePublished - May 7 2016
Event34th Annual Conference on Human Factors in Computing Systems, CHI 2016 - San Jose, United States
Duration: May 7 2016May 12 2016

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other34th Annual Conference on Human Factors in Computing Systems, CHI 2016
CountryUnited States
CitySan Jose
Period5/7/165/12/16

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Keywords

  • Bias
  • Controversy
  • Online opinion space
  • Opinion minority
  • Social media
  • Social opinion
  • Twitter

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Liao, Q. V., Fu, W. T., & Strohmaier, M. (2016). #Snowden: Understanding biases introduced by behavioral differences of opinion groups on social media. In CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems (pp. 3352-3363). (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/2858036.2858422