Presentation 2012-02-03
Relation analysis of high degree users on Twitter by using follow similarity
Akihiro KOIDE, Kazumi SAITO, Fujio TORIUMI, Kazuhiro KAZAMA,
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Abstract(in English) In this paper, as the first step to construct user models on Twitter, we focus on the high degree users who are considered as main rule players in Twitter's follow network, and we analyze the relation among these high degree users based on a follow similarity measure. Our experimental results show that the high in-degree users can be clearly classified into two groups, i.e., low out-degree users and high out-degree users, while the high out-degree users form only one group, i.e., only high in-degree users.
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Keyword(in English) Twitter / complex network / follow network / degree / F-value / Jaccard coefficient
Paper # NLC2011-62
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Committee NLC
Conference Date 2012/1/26(1days)
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Paper Information
Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Relation analysis of high degree users on Twitter by using follow similarity
Sub Title (in English)
Keyword(1) Twitter
Keyword(2) complex network
Keyword(3) follow network
Keyword(4) degree
Keyword(5) F-value
Keyword(6) Jaccard coefficient
1st Author's Name Akihiro KOIDE
1st Author's Affiliation Graduate School of Management and Information of Innovation, University of Shizuoka()
2nd Author's Name Kazumi SAITO
2nd Author's Affiliation Graduate School of Management and Information of Innovation, University of Shizuoka
3rd Author's Name Fujio TORIUMI
3rd Author's Affiliation Graduate School of Information Science, Nagoya University
4th Author's Name Kazuhiro KAZAMA
4th Author's Affiliation NTT Network Innovation Laboratories, Nippon Telegraph and Telephone Corporation
Date 2012-02-03
Paper # NLC2011-62
Volume (vol) vol.111
Number (no) 427
Page pp.pp.-
#Pages 6
Date of Issue