Developing Cross-Lingual Sentiment Analysis Of Malay Twitter Data Using Lexicon-Based Approach

Zabha, Nur Imanina and Ayop, Zakiah and Anawar, Syarulnaziah and Hamid, Erman and Zainal Abidin, Zaheera (2019) Developing Cross-Lingual Sentiment Analysis Of Malay Twitter Data Using Lexicon-Based Approach. International Journal of Advanced Computer Science and Applications, 10 (1). pp. 346-351. ISSN 2158-107X

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Abstract

Sentiment analysis is a process of detecting and classifying sentiments into positive, negative or neutral. Most sentiment analysis research focus on English lexicon vocabularies. However, Malay is still under-resourced. Research of sentiment analysis in Malaysia social media is challenging due to mixed language usage of English and Malay. The objective of this study was to develop a cross-lingual sentiment analysis using lexicon based approach. Two lexicons of languages are combined in the system, then, the Twitter data were collected and the results were determined using graph. The results showed that the classifier was able to determine the sentiments. This study is significant for companies and governments to understand people's opinion on social network especially in Malay speaking regions.

Item Type:	Article
Uncontrolled Keywords:	Cross-lingual, Lexiconbased approach, Opinion mining, Sentiment analysis
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Sabariah Ismail
Date Deposited:	03 Dec 2020 16:02
Last Modified:	03 Dec 2020 16:02
URI:	http://eprints.utem.edu.my/id/eprint/24452
Statistic Details:	View Download Statistic

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