Presentation | 2012-09-27 Analysis of lnfluential Tweets on Twitter Using N-gram Model Yuki NAKADA, Eiji KAMIOKA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | With the remarkable development of social networking services in recent years,anyone can easily share their information. These services can be used for corporate advertising (PR) as well as building individual influences on the public.In this paper,grammatical feature extraction from posted sentences will be performed and sentence pattens which can commonly be posted by anyone will be derived. Grammatical features used in this paper are the ratio of column and the percentage of part-of-speech in the posted sentences. In addition to these investigations,discussions and comparisons on different aspects of general and influential posts will be presented. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | SNS / Web mining / N-gram model |
Paper # | MoMuC2012-20 |
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Committee | MoMuC |
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Conference Date | 2012/9/20(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Mobile Multimedia Communications(MoMuC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Analysis of lnfluential Tweets on Twitter Using N-gram Model |
Sub Title (in English) | |
Keyword(1) | SNS |
Keyword(2) | Web mining |
Keyword(3) | N-gram model |
1st Author's Name | Yuki NAKADA |
1st Author's Affiliation | Graduate School of Engineering and Science,Shibaura Institute of Technology() |
2nd Author's Name | Eiji KAMIOKA |
2nd Author's Affiliation | Graduate School of Engineering and Science,Shibaura Institute of Technology |
Date | 2012-09-27 |
Paper # | MoMuC2012-20 |
Volume (vol) | vol.112 |
Number (no) | 219 |
Page | pp.pp.- |
#Pages | 6 |
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