How algorithms shape the distribution of political advertising: Case studies of facebook, google, and TikTok

Orestis Papakyriakopoulos, Christelle Tessono, Arvind Narayanan, Mihir Kshirsagar

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

Abstract

Online platforms play an increasingly important role in shaping democracy by influencing the distribution of political information to the electorate. In recent years, political campaigns have spent heavily on the platforms' algorithmic tools to target voters with online advertising. While the public interest in understanding how platforms perform the task of shaping the political discourse has never been higher, the efforts of the major platforms to make the necessary disclosures to understand their practices falls woefully short. In this study, we collect and analyze a dataset containing over 800,000 ads and 2.5 million videos about the 2020 U.S. presidential election from Facebook, Google, and TikTok. We conduct the first large scale data analysis of public data to critically evaluate how these platforms amplified or moderated the distribution of political advertisements. We conclude with recommendations for how to improve the disclosures so that the public can hold the platforms and political advertisers accountable.

Original languageEnglish (US)
Title of host publicationAIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
PublisherAssociation for Computing Machinery, Inc
Pages532-546
Number of pages15
ISBN (Electronic)9781450392471
DOIs
StatePublished - Jul 26 2022
Event5th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, AIES 2022 - Oxford, United Kingdom
Duration: Aug 1 2022Aug 3 2022

Publication series

NameAIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Conference

Conference5th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, AIES 2022
Country/TerritoryUnited Kingdom
CityOxford
Period8/1/228/3/22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Social Sciences (miscellaneous)

Keywords

  • accountability
  • algorithmic auditing
  • algorithmic targeting
  • interpretability
  • political advertising
  • political speech
  • regulation

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