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...

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主要作者: Abdullah Sani, Aidil Amirul Safwan
格式: Thesis
語言:English
出版: 2020
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在線閱讀:https://ir.uitm.edu.my/id/eprint/31488/1/31488.pdf
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