Visualizing the reputation of Malaysian communication service providers through twitter sentiment analysis using naïve bayes / Aidil Amirul Safwan Abdullah Sani

A text classifier model optimized for short snippets like tweets is developed to make bilingual sentiment analysis possible. The two languages explored are Bahasa Malaysia and English, since they are the two most commonly spoken languages in Malaysia. The classifier model is trained and tested on a...

詳細記述

保存先:
書誌詳細
第一著者: Abdullah Sani, Aidil Amirul Safwan
フォーマット: 学位論文
言語:English
出版事項: 2020
主題:
オンライン・アクセス:http://ir.uitm.edu.my/id/eprint/31488/1/31488.pdf
http://ir.uitm.edu.my/id/eprint/31488/
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