Sentiment classification of unstructured data using lexical based techniques

• Main Authors: Shamsudin, Nurul Fathiyah, Basiron, Halizah, Saaya, Zurina, Abdul Rahman, Ahmad Fadzli Nizam, Zakaria, Mohd Hafiz, Hassim, Nurulhalim
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2015
• Online Access: http://eprints.utem.edu.my/id/eprint/28201/2/0097916082024154561020.pdf; http://eprints.utem.edu.my/id/eprint/28201/; https://journals.utm.my/jurnalteknologi/article/view/6497; https://doi.org/10.11113/jt.v77.6497

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.