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ID 113910
Author
Tsuchiya, Seiji Doshisha University
Keywords
Slang
Topic analysis
Time-series analkysis
Content Type
Journal Article
Description
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.
Journal Title
International Journal of Advanced Intelligence
ISSN
18833918
Publisher
AIA International Advanced Information Institute
Volume
8
Issue
1
Start Page
84
End Page
98
Published Date
2016-05
EDB ID
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology