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The Uneven Decline of Collective Knowledge Production: Evidence from Stack Overflow After Generative AI

Source
arxiv.org
Author
Myokyung Han, Taegyoon Kim, Jinhyuk Yun, Lanu Kim
Date

Context

The questions remaining on Stack Overflow shifted toward harder and less common problems after ChatGPT's release, according to a study of posting patterns. Its analysis of more than two million questions from 2020 to 2025, centered on Python-tagged posts, found that easy questions declined sharply while difficult ones became more common, and that topics with plenty of earlier coverage lost share to rarer ones.

The researchers used earlier question volume to estimate how well covered a topic was, and checked difficulty through question classification and the complexity of code in questions. The decline in easy questions was concentrated in well-covered topics. These are shares of questions, so a larger share of difficult questions does not by itself mean more difficult questions in absolute numbers. The findings concern one community and one field, and do not establish where each missing question went.

Key takeaways · AI-distilled
  • The authors analyze more than two million Stack Overflow questions posted between 2020 and 2025, treating the release of ChatGPT-3.5 as a natural shock and tracking two dimensions: question difficulty and how much data exists for a topic.
  • The drop in easy questions was accompanied by rising code complexity in posted questions, which the authors treat as corroboration that the remaining traffic skews harder.
  • The two effects interact: the decline in easy questions is concentrated in data-rich domains, while difficult questions increased regardless of how much data a topic had.
  • The pattern extends beyond Python to other programming languages, and more prevalent languages show sharper shifts, according to the paper.
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