Crowd Wisdom: The Impact of Opinion Diversity and Participant Independence on Crowd Performance

Recent advances in information technologies such as Web 2.0 have dramatically expanded the use of crowd wisdom in dealing with a wide range of problems. Prior research confirms the importance of crowd wisdom in the context of stock markets, but fails to investigate the impact of crowd characteristics on crowd performance. We study the influence of opinion diversity and participant independence on the crowd performance in the context of online investment communities. Instead of using a survey research methodology, which is usually time-consuming and limited to a small sample, we develop text mining based measures for the variables in our research model. The empirical results show that opinion distance is positively related to crowd performance. Opinion content similarity and participant dependence are negatively associated with crowd performance. Crowd size significantly moderates the relationships between crowd characteristics and crowd performance. Related theoretical and practical implications are also discussed.

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