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ID 113246
著者
Matsuoka, Masaya Tokushima University
資料タイプ
学術雑誌論文
抄録
Recently, the authors often see words such as youth slang, neologism and Internet slang on social networking sites (SNSs) that are not registered on dictionaries. Since the documents posted to SNSs include a lot of fresh information, they are thought to be useful for collecting information. It is important to analyse these words (hereinafter referred to as ‘slang’) and capture their features for the improvement of the accuracy of automatic information collection. This study aims to analyse what features can be observed in slang by focusing on the topic. They construct topic models from document groups including target slang on Twitter by latent Dirichlet allocation. With the models, they chronologically the analyse change of topics during a certain period of time to find out the difference in the features between slang and general words. Then, they propose a slang classification method based on the change of features.
掲載誌名
CAAI Transactions on Intelligence Technology
ISSN
24682322
出版者
The Institution of Engineering and Technology
4
1
開始ページ
64
終了ページ
71
発行日
2019-01-18
権利情報
This is an open access article published by the IET, Chinese Association for Artificial Intelligence and Chongqing University of Technology under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
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出版社版DOI
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言語
eng
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出版社版
部局
理工学系