Understanding public sentiment of Malaysians on the 2023 Israel-Hamas war: a case study of the Al-ahliarab hospital explosion on Twitter

Recently, an international conflict has been reignited between two prominent political powers: Israel and Hamas. Public discourse about the 2023 Israel-Hamas war has been prevalent on social media platforms. The Malaysian government has showed support towards Palestine during this conflict, but th...

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Bibliographic Details
Main Author: Arvind, Matheven
Format: Final Year Project / Dissertation / Thesis
Published: 2024
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Online Access:http://eprints.utar.edu.my/6396/1/Final_Dissertation_Arvind_Matheven_(clean).pdf
http://eprints.utar.edu.my/6396/
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Summary:Recently, an international conflict has been reignited between two prominent political powers: Israel and Hamas. Public discourse about the 2023 Israel-Hamas war has been prevalent on social media platforms. The Malaysian government has showed support towards Palestine during this conflict, but the possibility of pro-Israel supporters may still exist among the Malaysian populace. The main research objectives of this paper are to distinguish Malaysian public sentiment towards the 2023 Israel-Hamas war, and to recognise the effects of narratives in news coverage regarding the 2023 Israel-Hamas war on the public sentiment of Malaysians. In this study, a quantitative research design is utilised while news framing theory operates as the backbone of this study. Data is collected from the social media platform named X, formerly known as Twitter. Specifically, responses on posts from verified local news sources will be targeted. According to the data collected, majority of Malaysians manifest a pro�Palestine sentiment, but it is proven that there are also more individuals who adopt a pro-Israel stance on the conflict compared to those who remain neutral towards the issue. Also, it was discovered that public sentiment is not influenced by narratives of media coverage based on patterns deciphered in the findings. KEYWORDS: Israel-Hamas war, Public sentiment, Twitter, News framing theory, Sentiment analysis.