Presentation 2013-06-22
Automatic Alignment of Tweets with Research Papers
Hikaru NAKAHASHI, Hidetsugu NANBA, Toshiyuki TAKEZAWA, Atsuhiro TAKASU,
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Abstract(in English) Recently, participants of academic conferences often post their comments for each research paper (presentation) to Twitter. Some of these comments are useful for understanding the papers from various viewpoints. Therefore, we have studied automatic alignment of tweets with research papers. The procedure consists of the following two steps: (1) alignment each tweet with a research paper and (2) classification of tweets for detecting useful ones. We conducted some experiments to confirm the effectiveness of our method. From the results, we obtained recall and precision scores of 0.5080 and 0.4853, respectively, for the alignment of tweets with research papers. We also obtained recall and precision scores of 0.4533 and 0.5782, respectively, for the classification of tweets.
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Keyword(in English) Twitter / research paper / DP matching / SVM
Paper # DE2013-17
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Committee DE
Conference Date 2013/6/15(1days)
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Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Automatic Alignment of Tweets with Research Papers
Sub Title (in English)
Keyword(1) Twitter
Keyword(2) research paper
Keyword(3) DP matching
Keyword(4) SVM
1st Author's Name Hikaru NAKAHASHI
1st Author's Affiliation Graduate School of Information Sciences, Hiroshima City University()
2nd Author's Name Hidetsugu NANBA
2nd Author's Affiliation National Institute of Informatics
3rd Author's Name Toshiyuki TAKEZAWA
3rd Author's Affiliation National Institute of Informatics
4th Author's Name Atsuhiro TAKASU
4th Author's Affiliation National Institute of Informatics
Date 2013-06-22
Paper # DE2013-17
Volume (vol) vol.113
Number (no) 105
Page pp.pp.-
#Pages 6
Date of Issue