Developing Cross-lingual Sentiment Analysis of Malay Twitter Data Using Lexicon-based Approach

被引：0

作者：

Zabha, Nur Imanina ^{[1
]}

Ayop, Zakiah ^{[1
]}

Anawar, Syarulnaziah ^{[1
]}

Hamid, Erman ^{[1
]}

Abidin, Zaheera Zainal ^{[1
]}

机构：

[1] Univ Teknikal Malaysia Melaka, Fac Informat & Commun Technol, Ctr Adv Comp Technol, Durian Tunggal 76100, Melaka, Malaysia

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2019年 / 10卷 / 01期

关键词：

Opinion Mining; Sentiment Analysis; Lexicon-based Approach; Cross-lingual;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：346 / 351

页数：6

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