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ID 113246
Author
Matsuoka, Masaya Tokushima University
Content Type
Journal Article
Description
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.
Journal Title
CAAI Transactions on Intelligence Technology
ISSN
24682322
Publisher
The Institution of Engineering and Technology
Volume
4
Issue
1
Start Page
64
End Page
71
Published Date
2019-01-18
Rights
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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DOI (Published Version)
URL ( Publisher's Version )
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology