Presentation 2011-12-16
A Study on Characteristics of Topic-Specific Information Cascade in Twitter
Geerajit RATTANARITNONT, Masashi TOYODA, Masaru KITSUREGAWA,
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Abstract(in English) In this paper, we study patterns of information diffusion and behaviors of participating users in Twitter. We investigate characteristics of hashtag cascade in various topics by exploiting distributions of user influence, which are cascade ratio, tweet ratio, and time interval. We show that topics of major hashtags can be characterized by these distributions. For example, people using political hashtags often influence many of their friends and continuously discuss on the topics. Our experiments also show that the hashtags can be roughly clustered into topics using only those measures, and miss-clustered hashtags have some special roles in their topics.
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Keyword(in English) Social network / Information diffusion / Web mining
Paper # DE2011-51
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Committee DE
Conference Date 2011/12/9(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Characteristics of Topic-Specific Information Cascade in Twitter
Sub Title (in English)
Keyword(1) Social network
Keyword(2) Information diffusion
Keyword(3) Web mining
1st Author's Name Geerajit RATTANARITNONT
1st Author's Affiliation Institute of Industrial Science The University of Tokyo()
2nd Author's Name Masashi TOYODA
2nd Author's Affiliation Institute of Industrial Science The University of Tokyo
3rd Author's Name Masaru KITSUREGAWA
3rd Author's Affiliation Institute of Industrial Science The University of Tokyo
Date 2011-12-16
Paper # DE2011-51
Volume (vol) vol.111
Number (no) 361
Page pp.pp.-
#Pages 6
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