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The Moderating Roles of Network Density and Redundancy in Lurking Behavior on User-Generated-Content Online Communities

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 787))

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Abstract

Sharing content is one of the important ways of information diffusion in online UGC (User-Generated Content), communities. Most of previous research on the sharing behavior focused on predicting the sharing behavior by the inherent characteristics of the posts. This study addressed the important role of social networking characteristics, including network structure and information density, on users’ sharing behavior. Based on a social network from a large UGC platform in China, this study analyzed the panel data of 10,000 users of their daily activities. The results showed that network density and redundancy jointly influenced users’ sharing behavior. This study contributes to social network theory by providing new empirical evidence on user-generated content diffusion in UGC community. In particular, it explained how network density moderating the effect of users on UGC diffusion. This study also had important management implications for platform managers to design effective product strategies to increase UGC diffusion.

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Author information

Authors and Affiliations

  1. Department of Marketing, Shenzhen University, Shenzhen, China

    Xingyu Chen, Yitong Wang, Xianqi Hu & Zhan Zhou

Authors
  1. Xingyu Chen
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  2. Yitong Wang
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  3. Xianqi Hu
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  4. Zhan Zhou
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Corresponding author

Correspondence to Xingyu Chen .

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Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Tareq Z. Ahram

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Chen, X., Wang, Y., Hu, X., Zhou, Z. (2019). The Moderating Roles of Network Density and Redundancy in Lurking Behavior on User-Generated-Content Online Communities. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-94229-2_41

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