Sentiment analysis of China-related news in The Star Online newspaper

Abstract

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.