Text Mining Analysis of Malaysia’s National Image in China Daily

This study takes October. 4. 2013, as a temporal dividing point, conducting a comparative analysis of news closely related to Malaysia in China Daily , over the 10 years before and after this date. The qualitative research software Leximancer 5.0 is employed for text mining analysis. The findings reveal that the themes in the news transitioned from relatively dispersed, generalised coverage to a more focused, in-depth exploration of major events and China-Malaysia cooperation. The primary social actors demonstrated minimal change over the 20 years but became increasingly focused. Sentiment analysis shows that reporting on Malaysia has predominantly been positive, with the proportion of positive sentiment showing an upward trend. However, some negative factors were also observed, such as a shift in the portrayal of the 6th Prime Minister of Malaysia , from positive to negative. Notably, although the MH370 incident was reported with a predominantly negative perspective, it did not persist for long. Positive sentiments towards all associated social actors, except Indonesia, have continued to grow, including China, Singapore, Australia, and ASEAN. This study portrays Malaysia as a promising partner in economic growth and development, an important player in regional and global relations, and a stable and enduring strategic ally. By employing an innovative combination of text mining techniques and discourse analysis, the research not only provides empirical evidence of the evolving discourse surrounding Malaysia but also offers methodological insights for applying computational tools in media studies. Keywords: national image construction; text mining analysis; qualitative research software; media discourse analysis; diachronic study

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Publication Details

Journal
3L The Southeast Asian Journal of English Language Studies
Published
2025-09-30
DOI
https://doi.org/10.17576/3l-2025-3103-05
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
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Text Mining Analysis of Malaysia’s National Image in China Daily

Mohd Azidan Abdul Jabar, Jie Zhang, Farhana Muslim Mohd Jali
3L The Southeast Asian Journal of English Language Studies
Sentiment Analysis and Opinion Mining
article

Text Mining Analysis of Malaysia’s National Image in China Daily

Mohd Azidan Abdul Jabar, Jie Zhang, Farhana Muslim Mohd Jali
article en

Abstract

This study takes October. 4. 2013, as a temporal dividing point, conducting a comparative analysis of news closely related to Malaysia in China Daily , over the 10 years before and after this date. The qualitative research software Leximancer 5.0 is employed for text mining analysis. The findings reveal that the themes in the news transitioned from relatively dispersed, generalised coverage to a more focused, in-depth exploration of major events and China-Malaysia cooperation. The primary social actors demonstrated minimal change over the 20 years but became increasingly focused. Sentiment analysis shows that reporting on Malaysia has predominantly been positive, with the proportion of positive sentiment showing an upward trend. However, some negative factors were also observed, such as a shift in the portrayal of the 6th Prime Minister of Malaysia , from positive to negative. Notably, although the MH370 incident was reported with a predominantly negative perspective, it did not persist for long. Positive sentiments towards all associated social actors, except Indonesia, have continued to grow, including China, Singapore, Australia, and ASEAN. This study portrays Malaysia as a promising partner in economic growth and development, an important player in regional and global relations, and a stable and enduring strategic ally. By employing an innovative combination of text mining techniques and discourse analysis, the research not only provides empirical evidence of the evolving discourse surrounding Malaysia but also offers methodological insights for applying computational tools in media studies. Keywords: national image construction; text mining analysis; qualitative research software; media discourse analysis; diachronic study

3L The Southeast Asian Journal of English Language StudiesVol. 31(3)
Universiti Putra Malaysia (MY)
Openalex Percentile: Top 86%
Sentiment Analysis and Opinion Mining
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Text Mining Analysis of Malaysia’s National Image in China Daily — Mohd Azidan Abdul Jabar, Jie Zhang, et al. · 3L The Southeast Asian Journal of English Language Studies (2025) | TGRS Research Map | TGRS