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  • All HBS Web  (65)
    • Faculty Publications  (10)

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    • All HBS Web  (65)
      • Faculty Publications  (10)

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      • May 2021
      • Article

      Ideology and Composition Among an Online Crowd: Evidence From Wikipedians

      By: Shane Greenstein, Grace Gu and Feng Zhu
      Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that...  View Details
      Keywords: User Segregation; Online Community; Contested Knowledge; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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      Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideology and Composition Among an Online Crowd: Evidence From Wikipedians." Management Science 67, no. 5 (May 2021): 3067–3086.
      • Article

      Conversational Receptiveness: Expressing Engagement with Opposing Views

      By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
      We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then...  View Details
      Keywords: Receptiveness; Natural Language Processing; Disagreement; Interpersonal Communication; Relationships; Conflict Management
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      Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
      • September 2018
      • Article

      Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia

      By: Shane Greenstein and Feng Zhu
      Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective,...  View Details
      Keywords: Online Community; Collective Intelligence; Wisdom Of Crowds; Bias; Wikipedia; Britannica; Knowledge Production; Knowledge Sharing; Knowledge Dissemination; Prejudice and Bias
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      Greenstein, Shane, and Feng Zhu. "Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia." MIS Quarterly 42, no. 3 (September 2018): 945–959.
      • November 7, 2016
      • Article

      How Wikipedia Keeps Political Discourse from Turning Ugly

      By: Shane Greenstein and Feng Zhu
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      Greenstein, Shane, and Feng Zhu. "How Wikipedia Keeps Political Discourse from Turning Ugly." Harvard Business Review (website) (November 7, 2016).
      • 2014
      • Other Unpublished Work

      Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia

      By: Shane Greenstein
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      Greenstein, Shane. "Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia." 2014.
      • May 2012 (Revised January 2013)
      • Case

      Wikipedia: Project Esperanza

      By: Mikolaj Jan Piskorski, Andreea Gorbatai and Tiona Zuzul
      In October 2006, Wikipedia was the largest volunteer-run on-line encyclopedia which could be freely read and edited by anyone with internet access. Within almost six years of its founding in 2001, the project had attracted hundreds of thousands of editors who had...  View Details
      Keywords: Web-enabled Application; Internet; Information Publishing; Social and Collaborative Networks; Groups and Teams; Publishing Industry; United States
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      Piskorski, Mikolaj Jan, Andreea Gorbatai, and Tiona Zuzul. "Wikipedia: Project Esperanza." Harvard Business School Case 712-493, May 2012. (Revised January 2013.)
      • Article

      Is Wikipedia Biased?

      By: Shane Greenstein and Feng Zhu
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      Greenstein, Shane, and Feng Zhu. "Is Wikipedia Biased?" American Economic Review: Papers and Proceedings 102, no. 3 (May 2012): 343–348.
      • 2011
      • Article

      Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia

      By: Michael Zhang and Feng Zhu
      In this paper, we examine the causal relationship between group size and incentives to contribute in the setting of Chinese Wikipedia, the Chinese language version of an online encyclopedia that relies entirely on voluntary contributions. The group at Chinese Wikipedia...  View Details
      Keywords: Rights; Motivation and Incentives; Internet and the Web; Valuation; Groups and Teams; Knowledge Sharing; Behavior; Satisfaction; Size; Government and Politics; Economics; Information Technology Industry; Hong Kong; Taiwan; Singapore
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      Zhang, Michael, and Feng Zhu. "Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia." American Economic Review 101, no. 4 (June 2011): 1601–1615.
      • February 2007 (Revised February 2007)
      • Case

      Wikipedia (A)

      By: Karim R. Lakhani and Andrew P. McAfee
      Wikipedia has emerged as a robust model for content production by volunteers working asynchronously on the Internet with a unconventional model for distributed decision making. The "Articles for Deletion" process in Wikipedia provides unique insight into the inner...  View Details
      Keywords: Information Publishing; Information Management; Internet and the Web; Information Technology; Globalization; Service Delivery; Knowledge Sharing; Knowledge Management; Information Industry; Information Technology Industry
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      Lakhani, Karim R., and Andrew P. McAfee. "Wikipedia (A)." Harvard Business School Multimedia/Video Case 607-712, February 2007. (Revised February 2007.)
      • Research Summary

      Overview

      By: Feng Zhu
      Professor Zhu’s research focuses on the design of platform business models and its impact on platform performance. Platforms have become central to our economy. A platform is a product or service that enables two or more customer groups to interact. For example,...  View Details
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