API AND BEYOND: DETECTING COORDINATED BEHAVIOURS IN FACEBOOK INTERACTIONS AROUND POLITICAL NEWS STORIES

  • Giglietto Fabio University of Urbino
  • Nicola Righetti University of Urbino
  • Giada Marino University of Urbino

Abstract

This proposal is a follow-up of the project “Mapping Italian News Media Political Coverage in the Lead-up to 2018 General Election” (MINE). MINE aimed at creating a comprehensive map of the political news coverage created by the Italian online news media in the lead-up to 2018 general election. The final report of the project highlighted how the populist narrative dominated the news (both in terms of volume of coverage and Facebook engagement), and pinpointed the diverging patterns of Facebook interactions employed by different partisan communities to amplify the reach of the contents aligned with their worldview by sharing the news stories on social media, while trying to reframe, through comments, the negative coverage of the party they support. These insights led to further questions concerning the nature of the observed diverging patterns of Facebook interactions around political news. In particular, we wondered if the observed patterns were the result of a spontaneous grassroots effort or instead of a strategically organised attempt to manipulate the online news media landscape in order to game platforms algorithms in support of specific viewpoints, candidates and parties. Data originally collected for MINE during 2018 via publically available Facebook API proved useful to identify the patterns, but fall short of providing compelling evidence on the nature of these behaviours. In order to shed some light on this question, we thus requested and obtained access to two additional datasets directly provided by Facebook and made available through the Social Science One (SSO) initiative.

Published
2019-10-31
How to Cite
Fabio, G., Righetti, N., & Marino, G. (2019). API AND BEYOND: DETECTING COORDINATED BEHAVIOURS IN FACEBOOK INTERACTIONS AROUND POLITICAL NEWS STORIES. AoIR Selected Papers of Internet Research, 2019. https://doi.org/10.5210/spir.v2019i0.10964
Section
Papers G