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The impact of individual attributes on knowledge diffusion in web forums

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Abstract

Web forums one of the most important Web 2.0 developments have become a useful platform for tracking and exploring knowledge diffusion among online users. Such networks are usually large, complex, and multi-dimensional, consisting of various types of nodes and ties. Therefore we use exponential random graph models to model online multi-dimensional knowledge diffusion and to systematically evaluate the impact of individual characteristics on knowledge diffusion networks. Experiments are conducted on a longitudinal dataset that covers one decade, drawn from the Yahoo! Finance Wal-Mart message board. The results show that reciprocal knowledge diffusion occurs in the forum; high-authority individuals play an important role in knowledge diffusion networks; a high level of online activity has a positive impact on knowledge diffusion; and polarized emotions have little influence on the knowledge diffusion processes. We conclude this paper with a discussion of how exponential random graph models could contribute to our understanding of the structure of online knowledge diffusion networks.

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Acknowledgments

The research is based upon work supported in part by the Defense Threat Reduction Agency (DTRA) under Grant No. HDTRA1-09-1-0058. Thanks to Sarah Marshall for her suggestions and comments.

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Authors and Affiliations

  1. School of Economics and Management, Tongji University, Shanghai, China

    Bing Wu

  2. Department of Management Information Systems, University of Arizona, Tucson, AZ, USA

    Shan Jiang & Hsinchun Chen

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  1. Bing Wu
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  2. Shan Jiang
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  3. Hsinchun Chen
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Correspondence to Bing Wu.

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Wu, B., Jiang, S. & Chen, H. The impact of individual attributes on knowledge diffusion in web forums. Qual Quant 49, 2221–2236 (2015). https://doi.org/10.1007/s11135-015-0240-y

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