Why You Follow: A Classification Scheme for Twitter Follow Links
by Atsushi Tanaka, Hikaru Takemura, Keishi Tajima
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.