mlsanityData to 14 Oct 2026

Follower--Followee Ratio Category and User Vector for Analyzing Following Behavior

arXiv 2210.13874 ↗First posted 25 Oct 2022cs.SIcited by 1

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Abstract (arXiv)

Analyzing following behavior is important in many applications. Following behavior may depend on the main intention of the follower. Users may either follow their friends or they may follow celebrities to know more about them. It is difficult to estimate users' intention from their following relationships. In this paper, we propose an approach to analyze following relationships. First, we investigated the similarity between users. Similar followers and followees are likely to be friends. However, when the follower and followee are not similar, it is likely that follower seeks to obtain more information on the followee. Second, we categorized users by the network structure. We then proposed analysis of following behavior based on similarity and category of users estimated from tweets and user data. We confirmed the feasibility of the proposed method through experiments. Finally, we examined users in different categories and analyzed their following behavior.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 25 Oct 2022.

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