Follower classification through social network analysis in Twitter

Abstract

Through 'Twitter', one of the Social Network Service, people can have relationships by using 'Follow', a function of Twitter. Every user has different purposes, so there are various 'Followers', These Followers follow somebody in favor of them or just to support them without reasons or to criticize or watch one's behavior or tweet(one's comments). In this paper, a Model is suggested that why they follow certain users by using network relations between followers. User's influential supporters and influential non-supporters are extracted and then supporters, neutrals, and non-supporters are classified by follower's retweet information, profile and recent tweet sentiment analysis. In order to verify this suggestion's validity, random 30,000 users who follow one of the 5 politicians are extracted to experiment. After the experiment, I got to know that supports from influential support-followers and influential nonsupport- followers and non-support-followers classification was effective. © 2013 Springer-Verlag.