The impact of individual attributes on knowledge diffusion in web forums

The impact of individual attributes on knowledge diffusion in web forums 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

The impact of individual attributes on knowledge diffusion in web forums

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Publisher
Springer Netherlands
Copyright
Copyright © 2015 by Springer Science+Business Media Dordrecht
Subject
Social Sciences, general; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-015-0240-y
Publisher site
See Article on Publisher Site

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.

Journal

Quality & QuantitySpringer Journals

Published: Jun 27, 2015

References

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