论文标题
追随者 - 遵循比率类别和用户向量用于分析以下行为
Follower--Followee Ratio Category and User Vector for Analyzing Following Behavior
论文作者
论文摘要
在许多应用中，分析以下行为很重要。以下行为可能取决于追随者的主要意图。用户可以关注他们的朋友，或者他们可能会跟随名人以了解更多有关他们的信息。从以下关系中估算用户的意图很难。在本文中，我们提出了一种分析以下关系的方法。首先，我们研究了用户之间的相似性。类似的追随者和关注者可能是朋友。但是，当追随者和关注者不相似时，追随者很可能寻求获得有关关注者的更多信息。其次，我们按网络结构对用户进行了分类。然后，我们根据根据推文和用户数据估算的用户的相似性和类别对以下行为进行了分析。我们通过实验证实了该方法的可行性。最后，我们检查了不同类别的用户，并分析了他们的以下行为。
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.
