Sentiment classification of unstructured data using lexical based techniques

Shamsudina, Nurul Fathiyah and Basiron, Halizah and Saaya, Zurina and Abdul Rahman, Ahmad Fadzli Nizam and Zakaria, Mohd Hafiz and Hassim, Nurulhalim (2014) Sentiment classification of unstructured data using lexical based techniques. Jurnal Teknologi, UTM, 2012, 77 (18). pp. 113-120. ISSN 0127-9696

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Abstract

Sentiment analysis is the computational study of people’s opinion or feedback, attitudes, and emotions toward entities, individuals, issues, events, topics and their attributes. There are many research conducted for other languages such as English, Spanish, French, and German. However, lack of research is conducted to harvest the information in Malay words and structure them into a meaningful data. The objective of this paper is to introduce a lexical based method in analysing sentiment of Facebook comments in Malay. Three types of lexical based techniques are implemented in order to identify the sentiment of Facebook comments. The techniques used are term counting, term score summation and average on comments. The comparison of accuracy, precision and recall for all techniques are computed. The result shows that the average on comments method outperforms the other two techniques

Item Type:	Article
Uncontrolled Keywords:	Sentiment analysis, lexical based approach, term counting, term score summation, average on sentence and average on comments
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Muhammad Afiz Ahmad
Date Deposited:	20 Sep 2017 08:39
Last Modified:	12 Jul 2023 12:54
URI:	http://eprints.utem.edu.my/id/eprint/19229
Statistic Details:	View Download Statistic

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