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

Platforms lack transparency about political ad distribution: The study found that Facebook, Google, and TikTok provide insufficient public disclosure about how their algorithms decide which political advertisements reach voters, making it difficult for the public to understand or scrutinize these practices during elections.

Scale of political advertising is massive and largely invisible: Researchers analyzed over 800,000 ads and 2.5 million videos related to the 2020 U.S. presidential election, revealing the enormous volume of political content being algorithmically distributed—most of which voters cannot easily see or understand how they were targeted.

Algorithms actively shape democratic discourse: The platforms' algorithmic tools don't neutrally distribute political information; they actively amplify or moderate which political advertisements reach different voter groups, giving platforms significant power over what information citizens encounter during elections.

Current disclosures fall "woefully short": The researchers concluded that platforms' existing efforts to reveal their political advertising practices are inadequate, preventing voters, researchers, and regulators from holding either the platforms or political advertisers accountable for their methods.

Better transparency is essential for democracy: The study recommends improved disclosure requirements so the public can understand and evaluate how algorithms influence the political information they receive, which is fundamental to informed democratic participation.