mlsanityData to 14 Oct 2026

Asymmetric Discourse Homogenization and Shared Language Technology: Evidence from Reddit

arXiv 2608.13674 ↗First posted 13 Aug 2026cs.CY cs.CL cs.SIcited by 0

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Abstract (arXiv)

I document an ideologically asymmetric break in the pre-existing diversification trend of political discourse, emerging around late 2022, using 6 million Reddit comments from two cross-partisan forums, 2019-2025. Conservative users experienced an interruption of their prior diversification trajectory; progressive users showed no comparable change. The asymmetry is consistent across estimation strategies (ITS, DiD, RDiT, propensity-score matching) and temporal aggregations. A daily-frequency permutation test over 2,377 candidate cutoff dates shows the ChatGPT threshold produces an unremarkable estimate (49.8th percentile): the shift builds gradually instead of breaking at a single date. A continuous cumulative LLM index, tracking AI exposure across seven model releases, remains significant under a quadratic trend specification that eliminates the binary estimate. A stayer analysis narrows the mechanism: the homogenization effect disappears when the sample is restricted to authors active throughout the study period, and the stayer confidence interval excludes within-author effects even a tenth the size of the full-sample estimate. The mechanism is most parsimoniously ecological (community-level discursive convergence) rather than individual-level AI adoption, though the data cannot cleanly separate this account from concurrent secular change.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 27 references that are in the map. First posted on arXiv 13 Aug 2026.

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References · 12

  1. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  2. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
  3. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 481
  4. 2024Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviewscited by 164
  5. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 148
  6. 2021Algorithmic Monoculture and Social Welfarecited by 100
  7. 2024Measuring Political Bias in Large Language Models: What Is Said and How It Is Saidcited by 89
  8. 2021The Effect of People Recommenders on Echo Chambers and Polarizationcited by 20
  9. 2024LLMs left, right, and center: Assessing GPT's capabilities to label political bias from web domainscited by 9
  10. 2023Evidence of Demographic rather than Ideological Segregation in News Discussion on Redditcited by 2
  11. 2024Ideological Fragmentation of the Social Media Ecosystem: From echo chambers to echo platformscited by 2
  12. 2025Modeling Political Discourse with Sentence-BERT and BERTopiccited by 1

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