Modeling and Analysis of Tag Co-occurrence Dynamics Using Yule-Simon process

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  • Sato Koya
    Graduate School of Systems and Information Engineering, University of Tsukuba
  • Oka Mizuki
    Graduate School of Systems and Information Engineering, University of Tsukuba
  • Hashimoto Yasuhiro
    Graduate School of Systems and Information Engineering, University of Tsukuba
  • Kato Kazuhiko
    Graduate School of Systems and Information Engineering, University of Tsukuba

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Other Title
  • Yule-Simon過程によるタグ共起ダイナミクスのモデル化と分析

Description

Social Tagging System (STS) which is one of the content management techniques is widely adopted in the online content sharing service. Using STS, users can give any strings (tags) to contents as annotations. It is important to know the usage of tag statistics for accomplishing an effective database design and the information navigation. The frequency of tag usage as well as their dynamics are similar to the ones found in the natural language. It is possible to reproduce the branching process of the tag dynamics using a classical model called Yule-Simon process. Another characteristic aspect of tags is the tag co-occurrence generated from the simultaneous use of tags. Using the tag co-occurrence, STS is able to reconstitute the hierarchy of tags, and recommend the tag which is probably used next. However, Yule-Simon process does not consider the tag co-occurrence and thus how the tag co-occurrence is generated from the model like Yule-Simon has not been addressed yet. In this paper, we propose to expand the Yule-Simon process to model the tag co-occurrence. From the point of view of network hierarchy, we confirm the similarity in the structure of the tag co-occurrence with the empirical data obtained from a social network service called ‘RoomClip’. The present result suggested that this simple model like extended Yule-Simon process generates the tag co-occurrence feature.

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