An enhanced lexicon-based approach for sentiment analysis: a case study on illegal immigration

Mehmood, Yasir and Balakrishnan, Vimala (2020) An enhanced lexicon-based approach for sentiment analysis: a case study on illegal immigration. Online Information Review, 44 (5). pp. 1097-1117. ISSN 1468-4527, DOI https://doi.org/10.1108/OIR-10-2018-0295.

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Abstract

Purpose Research on sentiment analysis were mostly conducted on product and services, resulting in scarcity of studies focusing on social issues, which may require different mechanisms due to the nature of the issue itself. This paper aims to address this gap by developing an enhanced lexicon-based approach. Design/methodology/approach An enhanced lexicon-based approach was employed using General Inquirer, incorporated with multi-level grammatical dependencies and the role of verb. Data on illegal immigration were gathered from Twitter for a period of three months, resulting in 694,141 tweets. Of these, 2,500 tweets were segregated into two datasets for evaluation purposes after filtering and pre-processing. Findings The enhanced approach outperformed ten online sentiment analysis tools with an overall accuracy of 81.4 and 82.3% for dataset 1 and 2, respectively as opposed to ten other sentiment analysis tools. Originality/value The study is novel in the sense that data pertaining to a social issue were used instead of products and services, which require different mechanism due to the nature of the issue itself.

Item Type: Article
Funders: UNSPECIFIED
Uncontrolled Keywords: Sentiment analysis; Lexicon-based; Social issue; Twitter; General inquirer
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science & Information Technology
Faculty of Computer Science & Information Technology > Department of Information System
Depositing User: Ms Zaharah Ramly
Date Deposited: 01 Dec 2023 00:28
Last Modified: 01 Dec 2023 00:28
URI: http://eprints.um.edu.my/id/eprint/36559

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