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TikTok quietly removed view counts for hashtags in January, after researchers used them to show the disparity in views of pro-Israel and pro-Palestinian videos

The change came after researchers cited TikTok's video-view counts to discuss the relative prominence of pro-Israel and pro-Palestinian videos on the app.

Washington Post Drew Harwell

Context & Ripple Effects

TikTok had already restricted Creative Center's hashtag-tracking tools after they were used to scrutinize Israel-Hamas-war content. Removing public hashtag view totals extends that retreat from easily accessible aggregate visibility.

The change also sits uneasily beside TikTok's earlier plan to open a research API to civil-society groups amid complaints about viral war content. The central question is shifting from whether data exists to who can independently inspect it.

First-order effects

  • Researchers, journalists, and users lose a simple public metric for comparing the reach associated with pro-Israel and pro-Palestinian hashtags.
  • TikTok reduces the visibility of a metric that had been used to support claims about relative content prominence on the platform.

Second-order effects

  • Outside analysis of hashtag reach will have to rely more on platform-provided research access, direct data collection, or narrower samples, making rapid public checks harder.
  • The move compounds the practical effect of Creative Center access restrictions for advertisers and watchdogs seeking aggregate hashtag signals.

Third-order effects

  • If platforms increasingly limit public engagement metrics while channeling scrutiny through controlled research interfaces, independent auditing of recommendation and moderation outcomes may become less reproducible.
  • The dispute reinforces that hashtag metrics are not merely product analytics: they can become contested evidence in politically charged claims about platform distribution.

The trend: Large social platforms are tightening access to aggregate content metrics as those metrics become evidence in debates over political visibility and algorithmic bias.