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Lexicon-Based Sentiment Analysis and Emotion Classification of Climate Change Related Tweets

Fagbola, Temitayo Matthew; Abayomi, Abdultaofeek; Mutanga, Murimo Bethel; Jugoo, Vikash

Authors

Abdultaofeek Abayomi

Murimo Bethel Mutanga

Vikash Jugoo



Abstract

The concerns for a potential future climate jeopardy has steered actions by youths globally to call the governments to immediately address challenges relating to climate change. In this paper, using natural language processing techniques in data science domain, we analyzed twitter micro-blogging streams to detect emotions and sentiments that surround the Global youth Climate Protest (GloClimePro) with respect to #ThisIsZeroHour, #ClimateJustice and #WeDontHaveTime hashtags. The analysis follows tweet scrapping, cleaning and preprocessing, extraction of GloClimePro-related items, sentiment analysis, emotion classification, and visualization. The results obtained reveal that most people expressed joy, anticipation and trust emotions in the #ThisIsZeroHour and #ClimateJustice action than the few who expressed disgust, sadness and surprise. #ClimateJustice conveys the most positive sentiments, followed by #ThisIsZeroHour and the #WeDontHaveTime. In all the evaluations, a considerable number of people express fear in the climate action and consequences. Thus, climate change stakeholders and policy makers should consider the sentiments and emotions expressed by people and incorporate such outcomes in their various programmes toward addressing the climate change challenges especially as it affects the ecosystem.

Citation

Fagbola, T. M., Abayomi, A., Mutanga, M. B., & Jugoo, V. (2022). Lexicon-Based Sentiment Analysis and Emotion Classification of Climate Change Related Tweets. In Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) (637-646). https://doi.org/10.1007/978-3-030-96302-6_60

Conference Name 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)
Conference Location Online
Start Date Dec 15, 2021
End Date Dec 17, 2021
Acceptance Date Nov 2, 2021
Online Publication Date Feb 22, 2022
Publication Date Feb 22, 2022
Deposit Date Jan 28, 2024
Publicly Available Date Feb 5, 2024
Publisher Springer
Pages 637-646
Series Title Lecture Notes in Networks and Systems
Series Number 17
Series ISSN 2367-3389
Book Title Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)
ISBN 9783030963019
DOI https://doi.org/10.1007/978-3-030-96302-6_60
Public URL https://hull-repository.worktribe.com/output/4161527

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