Ideological Segregation among Online Collaborators: Evidence from Wikipedians

Shane Greenstein, Yuan Gu () and Feng Zhu ()
Additional contact information
Yuan Gu: Harvard Business School
Feng Zhu: Harvard Business School, Technology and Operations Management Unit

No 17-028, Harvard Business School Working Papers from Harvard Business School

Abstract: Do online communities segregate into separate conversations about "contestable knowledge"? We analyze the contributors of biased and slanted content in Wikipedia articles about U.S. politics, and focus on two research questions: (1) Do contributors display tendencies to contribute to topics with similar or opposing bias and slant? (2) Do contributors learn from experience with extreme or neutral content, and does that experience change the slant and bias of their contributions over time? Despite heterogeneity in contributors and their contributions, we find an overall trend towards less segregated conversations. Contributors tend to edit articles with slants that are the opposite of their own views, and the slant from experienced contributors becomes less extreme over time. The experienced contributors with the most extreme biases decline the most. We also find some significant differences between Republicans and Democrats.

Pages: 49 pages
Date: 2016-10, Revised 2017-03
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Working Paper: Ideological Segregation among Online Collaborators: Evidence from Wikipedians (2016)
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