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Why You Follow: A Classification Scheme for Twitter Follow Links

by Atsushi Tanaka, Hikaru Takemura, Keishi Tajima

Abstract

Twitter is used for various purposes, such as, information publishing/gathering, open discussions, and personal communications. As a result, there are various types of follow links. In this paper, we propose a scheme for classifying follow links according to the followers' intention. The scheme consists of three axes: user-orientation, content-orientation, and mutuality. The combination of these three axes can classify most major types of follow links. Our experimental results suggest that the type of a follow link does not solely depend on the type of the followee nor solely on the type of the follower. The results also suggest that the proposed three axes are highly independent of one another.

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BibTex entry

Keywords

micro-blogging, social network, link classification
Published in Proc. of ACM Hypertext, pp.324-326, Santiago, Chile, 2014


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