Presentation 2014-10-09
Social Popularity Score: Predicting Numbers of Views, Comments, and Favorites of Social Photos Using Only Annotations
Shumpei SANO, Toshihiko YAMASAKI, Kiyoharu AIZAWA,
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Abstract(in English) In this paper, we propose an algorithm to predict the social popularity (i.e., the numbers of views, comments, and favorites) of content on social networking services using only text annotations. Instead of analyzing image/video content, we try to estimate social popularity by a combination of weight vectors obtained from a support vector regression (SVR) and tag frequency. Since our proposed algorithm uses text annotations instead of image/video features, its computational cost is small. As a result, we can estimate social popularity more efficiently than previously proposed methods. Furthermore, tags that significantly affect social popularity can be extracted using our algorithm.
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Keyword(in English) Social media / social popularity / folksonomy / regression / classification
Paper # MVE2014-40
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Committee MVE
Conference Date 2014/10/2(1days)
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Registration To Media Experience and Virtual Environment (MVE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Social Popularity Score: Predicting Numbers of Views, Comments, and Favorites of Social Photos Using Only Annotations
Sub Title (in English)
Keyword(1) Social media
Keyword(2) social popularity
Keyword(3) folksonomy
Keyword(4) regression
Keyword(5) classification
1st Author's Name Shumpei SANO
1st Author's Affiliation Department of Information and Communication Engineering, The University of Tokyo()
2nd Author's Name Toshihiko YAMASAKI
2nd Author's Affiliation Department of Information and Communication Engineering, The University of Tokyo
3rd Author's Name Kiyoharu AIZAWA
3rd Author's Affiliation Department of Information and Communication Engineering, The University of Tokyo
Date 2014-10-09
Paper # MVE2014-40
Volume (vol) vol.114
Number (no) 239
Page pp.pp.-
#Pages 6
Date of Issue