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

How Algorithms Shape the Distribution of Political Advertising: Case Studies of Facebook, Google, and TikTok