Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

2-2013

Abstract

This study investigates unfollow behavior in Twitter, i.e. people removing others from their Twitter following lists. Considering the interdependency and dynamics of unfollow decisions, we use actor-oriented modeling (SIENA) to examine the impacts of reciprocity, status, embeddedness, homophily, and informativeness on tie dissolution. Focusing on ordinary users in tightly-knitted user groups, the results show that relational properties play key roles in the emergence of unfollow behavior: mutual following relations and common followees reduce the likelihood of unfollowing. And unfollow tends to be reciprocal: when a user is unfollowed by someone, he or she will unfollow back. However, there is no evidence of the impacts of homophily based on common interests and informativeness of interactions. The findings suggest that Twitter has many heterogeneous user groups and relational and informational factors may not be applicable universally.

Keywords

Unfollow relations, Tie dissolution, Twitter, Actor-oriented modeling (SIENA), Snowball sampling.

Discipline

Numerical Analysis and Scientific Computing | Social and Behavioral Sciences | Social Media

Research Areas

Data Science and Engineering

Publication

Proceedings of the 2nd ACM Conference on Computer Supported Cooperative Work, CSCW 2013, San Antonio, TX, United States, February 23-27

First Page

871

Last Page

876

ISBN

978145031331-5

Identifier

10.1145/2441776.2441875

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/2441776.2441875

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