  When a re-election rally for the U.S. president drew smaller crowds than
expected in Tulsa, Oklahoma, many people attributed the low turnout to
collective action organized by TikTok users. Motivated by TikTok's surge in
popularity and its growing sociopolitical implications, this work explores the
role of TikTok's recommender algorithm in amplifying call-to-action videos that
promoted collective action against the Tulsa rally. We analyze call-to-action
videos from more than 600 TikTok users and compare the visibility (i.e. play
count) of these videos with other videos published by the same users. Evidence
suggests that Tulsa-related videos generally received more plays, and in some
cases the amplification was dramatic. For example, one user's call-to-action
video was played over 2 million times, but no other video by the user exceeded
100,000 plays, and the user had fewer than 20,000 followers. Statistical
modeling suggests that the increased play count is explained by increased
engagement rather than any systematic amplification of call-to-action videos.
We conclude by discussing the implications of recommender algorithms amplifying
sociopolitical messages, and motivate several promising areas for future work.
