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Sentiment community detection: exploring sentiments and relationships in social networks

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Abstract

Social networking sites (SNS), which allow users to express opinions on products/services, have become an important channel and platform for enterprises to acquire and trace users’ sentiments in order to design appropriate business strategies and online marketing campaigns. However, with the large number of users and complex user relationships on SNS, effectively capturing these sentiments for business decision support is still a big challenge. In this study we introduce the concept of “Sentiment Community,” a group of users who are closely connected and highly consistent in their sentiments about one product/service. Discovering such sentiment communities would be very valuable to enterprises for customer segmentation and target marketing. Taking into account both connections and sentiments, we propose two methods to discover sentiment communities by adopting the optimization models of semi-definite programming (SDP). Our experimental evaluations demonstrated great performances for the proposed methods. This study opens the doors to effectively explore users’ sentiments on SNS for business decision making.

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Acknowledgements

The authors thank the editors, Prof. Westland, Zhao, Xie, Xiao and Fan, and the three anonymous reviewers for helpful feedback. Kaiquan Xu acknowledges financial support from the National Science Foundation of China [NSF 71301071, 71572074], the Natural Science Foundation of Jiangsu Province [BK20130590], and Yizhen wu acknowledges financial support from the National Science Foundation of China [NSF 71272098]. All remaining errors are the authors’ own.

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Authors and Affiliations

  1. College of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China

    Dong Wang

  2. College of Business & Economics, Western Washington University, Bellingham, WA, 98229, USA

    Jiexun Li

  3. Department of Marketing & eBusiness, School of Business, Nanjing University, Nanjing, 210093, China

    Kaiquan Xu & Yizhen Wu

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  1. Dong Wang
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  2. Jiexun Li
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Correspondence to Kaiquan Xu or Yizhen Wu.

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Wang, D., Li, J., Xu, K. et al. Sentiment community detection: exploring sentiments and relationships in social networks. Electron Commer Res 17, 103–132 (2017). https://doi.org/10.1007/s10660-016-9233-8

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