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Identifying Implicit and Explicit Relationships Through User Activities in Social Media
Journal article   Peer reviewed

Identifying Implicit and Explicit Relationships Through User Activities in Social Media

Christopher C Yang, Xuning Tang, Qizhi Dai, Haodong Yang and Ling Jiang
International journal of electronic commerce, v 18(2)
01 Dec 2013

Abstract

social commerce homophily theory implicit relationships social network analysis Explicit relationships temporal analysis social media
Social commerce has emerged as a new paradigm of commerce due to the advancement and application of Web 2.0 technologies including social media sites. Social media sites provide a valuable opportunity for social interactions between electronic commerce consumers as well as between consumers and businesses. Although the number of users and interactions is large in social media, the social networks extracted from explicit user interactions are usually sparse. Hence, the result obtained through the analysis of the extracted network is not always useful because many potential ties in the social network are not captured by the explicit interactions between users. In this work, we propose a temporal analysis technique to identify implicit relationships that supplement the explicit relationships identified through the social media interaction functions. Our method is based on the homophily theory developed by McPherson, Smith-Lovin, and Cook [31]. We have conducted experiments to evaluate the effectiveness of the identified implicit relationships and the integration of implicit and explicit relationships. The results indicate that our proposed techniques are effective and achieve a higher accuracy. Our results prove the importance of implicit relationships in deriving complete online social networks that are the foundation for understanding online user communities and social network analysis. Our techniques can be applied to improve effectiveness of product and friend recommendation in social commerce.

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Web of Science research areas
Business
Computer Science, Software Engineering
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