Measuring polarization in Twitter enabled in online political conversation: The case of 2016 US Presidential election

S. Primario, D. Borrelli, G. Zollo, L. Iandoli, C. Lipizzi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

Political Polarization is the divergence of attitudes toward ideological extremes and it is more likely to happen in groups of like-minded individuals. We measured polarization on Twitter during the 2016 United States Presidential elections, analyzing Twitter back- channeling conversations occurring during the three Presidential debates. The polarization metric we use is based on an existing metaphor of the electric dipole. In each debate the polarization dynamic followed a U- shaped pattern, with polarization being high at the beginning of the debate, decreasing over time, and finally bouncing back to a value that was higher than the initial one. The temporary decline of polarization is due to the increase in interaction with participants holding opposite opinions, but apparently this interaction is more conducive to confrontation than to revision of existing beliefs. We argue that the characteristics of Twitter are generally conducive to polarized and manipulable online debate.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Information Reuse and Integration, IRI 2017
EditorsLatifur Khan, Balaji Palanisamy, Chengcui Zhang, Sahra Sedigh Sarvestani
Pages607-613
Number of pages7
ISBN (Electronic)9781538615621
DOIs
StatePublished - 8 Nov 2017
Event18th IEEE International Conference on Information Reuse and Integration, IRI 2017 - San Diego, United States
Duration: 4 Aug 20176 Aug 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Information Reuse and Integration, IRI 2017
Volume2017-January

Conference

Conference18th IEEE International Conference on Information Reuse and Integration, IRI 2017
Country/TerritoryUnited States
CitySan Diego
Period4/08/176/08/17

Keywords

  • Conversational analysis
  • E-politics
  • Polarization
  • Social media
  • Twitter

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