Asymmetric Discourse Homogenization and Shared Language Technology: Evidence from Reddit
- URL: http://arxiv.org/abs/2608.13674v1
- Date: Thu, 13 Aug 2026 18:13:35 GMT
- Title: Asymmetric Discourse Homogenization and Shared Language Technology: Evidence from Reddit
- Abstract summary: I document an ideologically asymmetric break in the pre-existing diversification trend of political discourse, emerging around late 2022.<n>Conservative users experienced an interruption of their prior diversification trajectory; progressive users showed no comparable change.<n>The asymmetry is consistent across estimation strategies (ITS, DiD, RDiT, propensity-score matching) and temporal aggregations.
- Score: 2.152401683177439
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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