Community Evolution Analysis Driven by Tag Events: The Special Perspective of New Tags

Jing Yang, Jun Wang () and Mengyang Gao
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Jing Yang: School of Economics and Management, Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191, China
Jun Wang: School of Economics and Management, Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191, China
Mengyang Gao: School of Economics and Management, Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191, China

Mathematics, 2023, vol. 11, issue 6, 1-18

Abstract: The type, quantity, and scale of social-tagging systems have grown constantly in recent years as users’ interest increases. Tags have important reference value in the study of networked communities since they typically represent user preference. This paper aims to examine how a tagging community evolves and to check the impact of new tags on evolution. Therefore, we proposed an improved evolution model for tag communities where tags constantly accumulate without withdrawal. Based on the model, we conducted an evolution analysis on three different tag communities with the datasets generated from the Delicious bookmarking system, CiteULike, and Douban. The results from Delicious emphasized that new individuals have an enormous influence on the community evolution, for they dominate the Form event, lead the early Split event, indirectly have a hand in the Merge event, and affect existing tags’ transfer when they flood into the system. Moreover, new tags are proved to be more influential in tagging relation data of CiteULike and Douban, where new tags dominate the Split event. The in-depth and detailed depiction of community evolution helps us understand the evolution process of tag communities and the crucial role of new tags.

Keywords: community evolution; tagging community; event-driven; group event; individual event; social tagging (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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