miklia/ai-slop-accusations-reddit-hackernews

AI slop accusations on Reddit and Hacker News, 2023-2026

Replication materials for Jason Miklian and John E. Katsos, "That's AI Slop, You Bot!" Studying Accusations, Evidence, and Credibility in Online Discourse Towards LLM-Generated Comments, https://arxiv.org/abs/2606.12073.

The data cover comments on Hacker News and 18 subreddits from January 2023 to 13 May 2026 that match a lexicon of AI-accusation language or a placebo lexicon of older inauthenticity terms ("shill", "astroturf", "sockpuppet"). They include 475,997 Reddit and 102,687 Hacker News comment identifiers, LLM classifications of 7,500 sampled comments, speech-act codes for 300 accusations, linguistic and sentiment measurements, a matched-control feature matrix, and the code that reproduces every table and figure in the paper.

Configurations

Config	Rows	Content
reddit_labels (default)	5,000	Reddit tier sample with saved labels: REAL, DISCLOSURE, NEUTRAL-REF, FP, AMBIGUOUS
hn_labels	2,500	Hacker News tier sample with labels and a short rationale
speech_acts	300	Speech-act codes for REAL Reddit accusations: SNEER, DISMISS, MOCKERY, GATEKEEP, STRUCTURAL_PROTEST
reddit_panel	736	Subreddit-month counts: scanned, AI-tier hits, placebo hits, tiers T1 to T5
hn_monthly	41	Hacker News month counts by tier
reddit_comment_ids	475,997	Retained Reddit comment identifiers with subreddit, timestamp, permalink and tier matches
hn_comment_ids	102,687	Retained Hacker News comment identifiers with timestamp, permalink and tier matches

Every file, with its fields, units and category meanings, is defined in replication/CODEBOOK.pdf and replication/CODEBOOK.md.

Reproduce the paper's results

cd replication
python -m pip install -r requirements.txt
python code/reproduce.py --self-test

The run uses Python 3.12, checks every input file against manifest.sha256, re-estimates the five regression models and writes the five tables, twelve supplements and four figures to output/reproduced. It makes no network or model calls.

Read before using

• Comment bodies are not distributed. The identifiers and permalinks let you retrieve the comments from the source platforms, subject to their terms.
• Usernames removed. The author column was dropped from data/raw_manifests/reddit_comment_ids.csv, data/raw_manifests/hn_comment_ids.csv and data/derived/h5_parents.csv, and manifest.sha256 was updated to match. The codebook rows describing author do not apply to this copy. No analysis uses the field, and the self-test passes on this copy.
• The labels are saved LLM classifications of what a comment says. They do not establish whether any target text was written by AI.
• Collection counters record scan events: 45,610,695 on Reddit and 11,766,175 on Hacker News. They do not record distinct comments.
• AskReddit was collected for the first day of each month and news and science for the first five days; the other subreddits cover full calendar months.

Citation

@article{miklian2026slop,
  title = {"That's AI Slop, You Bot!" Studying Accusations, Evidence, and Credibility in Online Discourse Towards LLM-Generated Comments},
  author = {Miklian, Jason and Katsos, John E.},
  journal = {arXiv preprint arXiv:2606.12073},
  year = {2026},
  url = {https://arxiv.org/abs/2606.12073}
}

License

Derived data and figures: CC BY 4.0. Code: MIT. See replication/LICENSE.md.