'Penerbit Universiti Kebangsaan Malaysia (UKM Press)'
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