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Sentiment Analysis of China-Related News in The Star Online Newspaper

Bibliographic Data

ID21185184
AuthorsHong Wu (0000-0001-6366-8831), Hong Ren Wu (0000-0002-7086-1629, National University of Malaysia), Kesumawati A Bakar (0000-0002-2787-5144, National University of Malaysia), Azhar Jaludin (0000-0002-7374-7936, National University of Malaysia), Norsimah Mat Awal (0000-0002-7693-2344, National University of Malaysia)
Year2022
Volume22
Issue3
Pages155-175
Publication date2022-08-30
Open AccessYes
TypeARTICLE
VenueGEMA Online Journal of Language Studies (JOURNAL)
Journal identifiersISSN: 1675-8021 • E-ISSN: 2550-2131
PublisherPenerbit Universiti Kebangsaan Malaysia (UKM Press) (PUBLISHER)
DOI10.17576/gema-2022-2203-09
OpenAlexW4293537595
LanguageEN
Citations received6

As China and Malaysia approach their 47th year of diplomatic relationships, cooperation and trust between the two countries have deepened in aspects ranging from politics to economy. Despite this mutual reliance, the relationship between Malaysia and China is not without its conflicts and these conflicts are often manifested in media reports. How China is presented in Malaysia news is a field that has been scarcely explored. As part of the research on media sentiment towards China, this research investigates the general sentiment of China-related news in Malaysian media through sentiment analysis of some selected news coverages. Selecting China-related news in The Star Online from 2012 to 2021 as the data for investigation,the Excel Add-in tool Azure Machine Learning was used to generate polarity of these news reports automatically and corpus tool Wordsmith was used for the analysis of news discourse. A total of 137,475 pieces of news have been collected as the research sample. The finding reveals that: 1) despite the large proportion of news with negative sentiment in China-related news in The Star Online , the monthly trend of sentiment shows a slight increase of positiveness over time; 2) an investigation into the keyword lists of three months with highest proportion of negativeness and collocates of the top keywords, however, shows that negative sentiment of the news may be due to a global conflict at that particular time and does not necessarily indicate negative sentiment towards China. A combination of sentiment analysis and corpus approach on the study of China-related news in Malaysian media enriches the study of news discourse from the perspective of corpus linguistics

Advertising · Business · China · Natural language processing · Newspaper · Political science · Politics · Sentiment analysis · Computer Science · Data Mining and Machine Learning Applications · Law · Mathematics · Multimedia Learning Systems · Sentiment Analysis and Opinion Mining

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Citations per year3
Citation span2024 - 2026 (3)
Highly citedNo

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