Sharp power in social media: Patterns from datasets across electoral campaigns
DOI:
https://doi.org/10.30722/anzjes.vol11.iss3.15110Keywords:
Canada, sharp power, machine learning, Twitter, social networks, political trolls, bots, foreign political meddlingAbstract
Using Christopher Walker’s and Jessica Ludwig’s ‘sharp power’ theoretical framework, and based on some preliminary findings from the May 2019 European Parliament election and the two 2019 rounds of elections in Israel, this article describes a novel method for the automatic detection of political trolls and bots active in Twitter in the October 2019 federal election in Canada. The research identified thousands of accounts invested in Canadian politics that presented a unique activity pattern, significantly different from accounts in a control group. The large-scale cross-cross-sectional approach enabled a distinctive perspective on foreign political meddling in Twitter during the recent federal election campaign. This
foreign political meddling, we argue, aims at manipulating and poisoning the democratic process and can challenge democracies and their values, as well as their societal resilience.
Downloads
Published
Issue
Section
License
Submission of an original manuscript to ANZJES will be taken to mean that it is an original work not previously published.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC BY-NC-ND) 4.0 Licence that allows others, including the author, to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the original author and initial publication in this journal.