Advancing Sentiment Analysis of Social Media Data: Unveiling Public Perception of Environmental Challenges in Malaysia

Anum Zahra, Lan Ma, Kok Wei Khong

    Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

    Abstract

    This study proposes a novel method for sentiment analysis of social media data, specifically X (formerly known as Twitter) data, and demonstrates its efficacy for predicting sentiments related to environmental issues. The proposed method employed state-of-the-art algorithms and machine learning approaches to perform the sentiment analysis of posts pertaining to environmental challenges in Malaysia, a country with significant social media usage in the Asia-Pacific region. The results showed that most of the posts analyzed were neutral in sentiment, suggesting a less polarized discourse on environmental challenges in Malaysia. The findings highlight the need for policy changes and environmental education to promote concern for environmental challenges and pro-environmental behavior among Malaysian residents. The proposed method is simple to use and accurately predicted sentiment from the X data. In addition to providing a valuable tool for researchers, the method has the potential to advance the field of sentiment analysis of social media data and be replicated in future research and practice.

    Original languageEnglish
    Title of host publicationSignals and Communication Technology
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages159-167
    Number of pages9
    DOIs
    Publication statusPublished - 2025

    Publication series

    NameSignals and Communication Technology
    VolumePart F76
    ISSN (Print)1860-4862
    ISSN (Electronic)1860-4870

    Keywords

    • Big data analytics
    • Environmental challenges
    • Sentiment analysis
    • Social media
    • Text mining

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Signal Processing
    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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