Abstract
Public perceptions on climate change is a paramount component in developing and conceiving mitigation and adaptation strategies towards climate change. An understanding of public perceptions on climate change may assist decision-makers in producing appropriate strategies to ameliorate the impacts of climate change. The aim of this study is to quantify public sentiment by examining the polarity of the public sentiments through sentiment analysis and corpus-driven approaches. A part of a specialised corpus namely the Malaysian Diachronic Climate Change Corpus (MyDCCC) was developed from an online newspaper published in Malaysia, and this data was used in the present study. Azure Machine Learning software was used to conduct the sentiment analysis in order to explore the polarity of public sentiments, while corpus- driven approach was employed to identify the sentiment lexicon. The analysis began with sentiment analysis approach to categorise the news articles into two sub-corpora; the negative sentiment sentiment and the positive sentiment. Positive and negative sentiment words were identified by matching the wordlists generated for each sub-corpus with the MPQA Subjectivity Lexicon. The results indicated that the majority of public sentiments were negative. From 59 news articles, 53 words were identified as negative sentiment, with an average polarity score of 0.056 and an overall polarity percentage of 90%. In contrast, only six words were identified as positive sentiment, with an average polarity score of 0.897 and an overall polarity percentage of 10%.The findings suggest that the public is reasonably aware of climate change, though their sentiments are predominantly negative. This negative stance is largely influenced by public dissatisfaction with how decision-makers are handling climate change issues. Paradoxically, these negative sentiments may serve as an indicator for decision-makers to improve their approach to addressing climate change. In conclusion, this study significantly contributes to research on public perceptions of climate change in the Malaysian context. It offers valuable insights for decision-makers, as understanding public sentiment can enhance their strategies to positively influence societal perceptions of climate change issues.
Biography
Prod. Nor Fariza Mohd Nor, is an Associate Professor at the Center of Research for Language and Linguistics, Faculty of Social Sciences and Humanities, National University of Malaysia (UKM). She received her Ph.D in Applied Linguistics from University of Malaya, and Master degree in English for Specific Purpose from the University of Warwick, U.K. Her Bachelor (Hons) degree is in Modern English Language and Education, from the University of Lancaster, U.K. Nor Fariza is a prolific writer and an active researcher, with her primary research interests encompassing media discourse and critical discourse studies. Her work includes analyses of the Malaysian Hansard corpus, as well as newspapers and social media corpora. She has published over 60 peer-reviewed papers, books, book chapters, and technical reports, and serves as a peer reviewer for high-impact journals such as PLOS ONE, SAGE Open, and Taylor & Francis. She has participated in 40 research projects within her areas of expertise. As a project leader, she has secured several international and national grants from various funding agencies, totaling nearly €70,000. She is currently engaged in multiple research projects with a strong focus on climate change, media linguistics, and the application of AI in teaching and learning. Her research in media linguistics employs sentiment analysis, corpus linguistics and word embedding techniques to capture sentiment analysis, collocations and the semantic meanings of words and their associations. The overarching aim of her research is to link language to Sustainable Development Goals (SDGs) in a way that benefits society.