Liang Lyu, James Siderius, Hannah Li, Daron Acemoglu, Daniel Huttenlocher, Asuman Ozdaglar
arXiv 2 Mar 2025 · cs.HC · 2 citations (OpenAlex)
arXiv:2503.00757 · PDF · DOI · OpenAlex · Extracted main text
How has Wikipedia activity changed for articles with content similar to ChatGPT following its introduction? We estimate the impact using differences-in-differences models, with dissimilar Wikipedia articles as a baseline for comparison, to examine how changes in voluntary knowledge contributions and information-seeking behavior differ by article content. Our analysis reveals that newly created, popular articles whose content overlaps with ChatGPT 3.5 saw a greater decline in editing and viewership after the November 2022 launch of ChatGPT than dissimilar articles did. These findings indicate heterogeneous substitution effects, where users selectively engage less with existing platforms when AI provides comparable content. This points to potential uneven impacts on the future of human-driven online knowledge contributions.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Philipp Singer, Florian Lemmerich, Robert West, Leila Zia, Ellery Wu… (2017) Why we read Wikipedia. In Proceedings of the 26th international conference on world wide web. 1591–1600 | 0.644 | 2 | 2 | 100% |
| 2 | Bo Xu and Dahui Li (2015) An empirical study of the motivations for content contribution and community participation in Wikipedia | 0.644 | 2 | 2 | 100% |
| 3 | Heng-Li Yang and Cheng-Yu Lai (2010) Motivations of Wikipedia content contributors | 0.644 | 2 | 2 | 100% |
| 4 | Gordon Burtch, Dokyun Lee, and Zhichen Chen (2024) The consequences of generative AI for online knowledge communities | 0.511 | 2 | 1 | 100% |
| 5 | Neal Reeves, Wenjie Yin, and Elena Simperl (2024) Exploring the Impact of ChatGPT on Wikipedia Engagement | 0.511 | 2 | 1 | 100% |
| 6 | Maria del Rio-Chanona, Nadzeya Laurentsyeva, and Johannes Wachs (2023) Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow | 0.511 | 2 | 1 | 100% |
| 7 | Guohou Shan and Liangfei Qiu (2023) Examining the impact of generative AI on users’ voluntary knowledge contribution: Evidence from a natural experiment on Stack Ov… | 0.511 | 2 | 1 | 100% |
| 8 | Sumit Kumar Dam, Choong Seon Hong, Yu Qiao, and Chaoning Zhang (2024) A complete survey on llm-based ai chatbots | 0.405 | 1 | 1 | 100% |
| 9 | Mark Glickman and Yi Zhang (2024) AI and generative AI for research discovery and summarization | 0.405 | 1 | 1 | 100% |
| 10 | OpenAI (2024) New embedding models and API updates | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 14 scored citations.