Online Journal of Communication and Media Technologies, Volume 15, Issue 2, Article No: e202512.
https://doi.org/10.30935/ojcmt/15990
ABSTRACT
This study aimed to identify the sentiments conveyed in international news coverage of the Kanjuruhan tragedy and examine how different perspectives on the catastrophe are portrayed across global news outlets. This study employed the appraisal framework to conduct a comprehensive analysis of the attitudes expressed in 10 international news articles covering the Kanjuruhan tragedy. The total data set comprised 8,605 words, within which 740 instances were identified as attitudinal sources, manifesting through words, phrases, and clauses. The analysis revealed that the most dominant type of attitude expressed was affect, accounting for 403 instances. This was followed by appreciation with 169 instances, and judgment with 166 instances. Notably, all types of attitudes were predominantly characterized by negative polarity. A significant finding is the presence of 326 negative instances of affect, which underscores the emotional tone of the coverage. Since affect relates to the emotional evaluation in the appraisal framework, the predominance of negative affect suggests that the news coverage largely evoked and reflected negative emotions associated with the tragedy. The findings demonstrate that the appraisal framework is a powerful tool for uncovering the underlying emotional and evaluative dimensions in news reporting. By highlighting the prevalent negative emotions and attitudes, the study provides insights into how the Kanjuruhan tragedy was framed in the international media, potentially influencing public perception and emotional response to the event. These insights can contribute to a deeper understanding of media representation and its impact on audience emotions and attitudes in the context of tragic events.
CITATION
Nurlela, Sinar, T. S., Rosa, R. N., Syahputra, F. P., Shafira, F., & Putri, D. M. (2025). Framed news positioning of attitude toward the Kanjuruhan tragedy: A corpus UAM tool analysis.
Online Journal of Communication and Media Technologies, 15(2), e202512.
https://doi.org/10.30935/ojcmt/15990