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ID 113910
著者
土屋, 誠司 Doshisha University
キーワード
Slang
Topic analysis
Time-series analkysis
資料タイプ
学術雑誌論文
抄録
Recently, with the increase in the number of users of Social Networking Sites (SNS), online communications have become more and more common, raising the possibility of using big data on SNS to analyze the diversity of language. Japanese language uses a variety of character types that are combined to create words and phrases. Therefore, it is difficult to morphologically analyze such words and phrases, even though morphological analysis is a basic process in natural language processing. Words and phrases that are not registered in morphological analysis dictionaries are usually not defined strictly, and their semantic interpretation seems to vary depending on the individual. In this study, we chronologically analyze the topics related to slang on Twitter. In this paper, as a validation experiment, we conducted a topic analysis experiment chronologically by using the sequential Tweet data and discussing the difference of topic change according to the slang types.
掲載誌名
International Journal of Advanced Intelligence
ISSN
18833918
出版者
AIA International Advanced Information Institute
8
1
開始ページ
84
終了ページ
98
発行日
2016-05
EDB ID
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
理工学系