Presentation 2014-01-24
A study on automatic classification method for Twitter "Big Data"
Akari YONEKAWA, Kenichi NAGAOKA,
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Abstract(in English) The purpose of this study is classifying tweets automatically and visualizing the results. Specifically, this research attempts to classify automatically sentiments on specific subject to positive or negative, and visualize the results to research the public opinion. To begin with, we build the supervised database, which is consisted by frequency of morphemes and consecutive morphemes, in a positive, negative or other tweet, from random sampled tweets classified manually. By depending on this supervised database, tweets are classified to positive, negative or others. The result of our experiment classifying general tweets shows accurate classification to a certain degree, especially when classifying to positive or negative without others. On the other hand, it is clarified that for specific subject, difficult examples have been seen in case that tweets include no any words which directly show its sentiment.
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Keyword(in English) Social media / Information visualization / Twitter / Morphological analysis / Big data
Paper # IN2013-132
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Committee IN
Conference Date 2014/1/16(1days)
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Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A study on automatic classification method for Twitter "Big Data"
Sub Title (in English)
Keyword(1) Social media
Keyword(2) Information visualization
Keyword(3) Twitter
Keyword(4) Morphological analysis
Keyword(5) Big data
1st Author's Name Akari YONEKAWA
1st Author's Affiliation Ishikawa National College of Technology()
2nd Author's Name Kenichi NAGAOKA
2nd Author's Affiliation Ishikawa National College of Technology
Date 2014-01-24
Paper # IN2013-132
Volume (vol) vol.113
Number (no) 389
Page pp.pp.-
#Pages 5
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