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Analysis of FCC net neutrality comments finds over 1M pro-repeal were likely faked and 99% of organic comments were in favor of keeping rules

I used natural language processing techniques to analyze net neutrality comments submitted to the FCC from April-October 2017, and the results were disturbing.

Hacker Noon Jeff Kao

Context & Ripple Effects

The FCC's 2017 net neutrality docket had already shown signs of contamination before this analysis: in May, its public comment system was flooded with 128K+ identical anti-net-neutrality comments submitted through the API, and by the August close the agency had received over 21M comments, many duplicates or spambot-generated. What was missing was a systematic answer to how much of the record was real.

This NLP analysis supplies that answer — over 1M pro-repeal comments likely faked, 99% of organic comments favoring keeping the rules — and the subsequent record largely vindicates it: a Stanford study found 99.7% of unique comments opposed the repeal, and a later investigation tied hundreds of thousands of fakes to D.C. media firm CQ Roll Call.

First-order effects

  • The FCC's repeal proceeding rests on a comment record whose pro-repeal side is now shown to be substantially synthetic, undermining the docket's claim to reflect public sentiment.
  • Organic commenters — 99% of whom favored keeping the rules — are effectively drowned out by machine-generated volume in the official record.

Second-order effects

  • Independent verification follows the anomaly: Stanford's later study replicates the finding at larger scale, and press investigations trace the fake comments to identifiable intermediaries like CQ Roll Call.
  • The trail eventually reaches funders — the NY AG's office attributes 8.5M fake comments to the largest US ISPs, turning a comment-quality story into an accountability question for named carriers.

Third-order effects

  • If bulk-generated comments can dominate a federal rulemaking record without consequence, notice-and-comment processes lose credibility as a measure of public opinion, pressuring agencies toward identity-verified submission systems.
  • Astroturfed comment campaigns become a recognized lobbying technique, shifting scrutiny from the policy docket itself to who pays for manufactured consensus.

The trend: Federal public-comment systems are becoming a contested channel where bot-driven astroturfing can outweigh genuine public input in high-stakes rulemakings.