Structural diversity effect on hashtag adoption in Twitter

Aihua Zhang, Mingxing Zheng and Bowen Pang

Physica A: Statistical Mechanics and its Applications, 2018, vol. 493, issue C, 267-275

Abstract: With online social network developing rapidly these years, user’ behavior in online social network has attracted a lot of attentions to it. In this paper, we study Twitter user’s behavior of hashtag adoption from the perspective of social contagion and focus on “structure diversity” effect on individual’s behavior in Twitter. We achieve data through Twitter’s API by crawling and build a users’ network to carry on empirical research. The Girvan–Newman (G–N) algorithm is used to analyze the structural diversity of user’s ego network, and Logistic regression model is adopted to examine the hypothesis. The findings of our empirical study indicate that user’ behavior in online social network is indeed influenced by his friends and his decision is significantly affected by the number of groups that these friends belong to, which we call structural diversity.

Keywords: Social network; Twitter; Structural diversity; Hashtag adoption (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:493:y:2018:i:c:p:267-275

DOI: 10.1016/j.physa.2017.09.075

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