A New Sentiment Analysis Model for Mixed Language using Contextual Lexicon

被引:0
|
作者
Mahadzir, Nurul Husna [1 ]
Razak, Nor Hafizah Abdul [1 ]
Omar, Mohd Faizal Mohd [2 ]
机构
[1] Univ Teknol MARA, Fac Comp & Math Sci, Sungai Petani Campus, Merbok 08400, Kedah, Malaysia
[2] Univ Utara Malaysia, Sch Quantitat Sci, Dept Decis Sci, Sintok 06010, Kedah, Malaysia
关键词
sentiment analysis; sentiment lexicon; contextual lexicon; mixed language; opinion mining; SOCIAL MEDIA; OPINION;
D O I
10.1109/ICRAIE51050.2020.9358286
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Sentiment analysis is one of the most active research areas in Natural Language Processing since early 2000. To date, sentiment analysis has been applied to various domains such as product, movie, sport and political reviews. Previously, the research in sentiment analysis area only concentrated on mining a single language. Nevertheless, due to the growth of multiple language usage in the form of writing and speaking, sentiment analysis activities have become more challenging. Many opinion keywords carry different polarities when they are used in different context, posing huge challenges to this field of research. Furthermore, in a social media environment where users tend to mix up languages, a lot of ambiguous content is present which makes a post difficult to be classified. Thus, this paper is a foray into the sentiment analysis for the context of mixed language.
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页数:5
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