Open Access

ARTICLE

MELex: The Construction of Malay-English Sentiment Lexicon

Nurul Husna Mahadzir¹, Mohd Faizal Omar², Mohd Nasrun Mohd Nawi^3,*, Anas A. Salameh⁴, Kasmaruddin Che Hussin⁵, Abid Sohail⁶

1 Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) Kedah, 08400, Merbok, Kedah, Malaysia
2 Department of Decision Sciences, School of Quantitative Sciences, Universiti Utara Malaysia, 06010, Kedah, Malaysia
3 Disaster Management of Institute, School of Technology Management and Logistic, Universiti Utara Malaysia, 06010, Kedah, Malaysia
4 Department of Management Information System, College of Business Administration, Prince Sattam Bin Abdulaziz University, 165, Al-Kharj, Saudi Arabia
5 Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Malaysia
6 Department of Computer Science, COMSATS University Islamabad, Lahore, Pakistan

* Corresponding Author: Mohd Nasrun Mohd Nawi. Email:

(This article belongs to the Special Issue: Computational Models for Pro-Smart Environments in Data Science Assisted IoT Systems)

Computers, Materials & Continua 2022, 71(1), 1789-1805. https://doi.org/10.32604/cmc.2022.021131

Received 24 June 2021; Accepted 12 August 2021; Issue published 03 November 2021

Abstract

Currently, the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon. Thus, this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis. In this study, a new lexicon for sentiment analysis is constructed. A detailed review of existing approaches has been conducted, and a new bilingual sentiment lexicon known as MELex (Malay-English Lexicon) has been generated. Constructing MELex involves three activities: seed words selection, polarity assignment, and synonym expansions. Our approach differs from previous works in that MELex can analyze text for the two most widely used languages in Malaysia, Malay, and English, with the accuracy achieved, is 90%. It is evaluated based on the experimentation and case study approaches where the affordable housing projects in Malaysia are selected as case projects. This finding has given an implication on the ability of MELex to analyze public sentiments in the Malaysian context. The novel aspects of this paper are two-fold. Firstly, it introduces the new technique in assigning the polarity score, and second, it improves the performance over the classification of mixed language content.

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