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Abstract·Keywords
This research analyzes media sentiment towards China and Korea with in-depth details. The study employs advanced Natural Language Processing (NLP) and sentiment analysis methods to analyze 11,598 documents, including news articles and reports. Through the analyses, the study detects sentiment patterns that reflect the complex geopolitical and economic interactions between the two nations. The study uses transformer-based models for accurate sentiment detection. The findings provide insights into how media narratives may shape and reflect international perceptions. Importantly, the study allows us to compare its outcomes with actual geopolitical events. It also highlights the capability of NLP techniques to understand the nuances of diplomatic relations, confirming the approach’s reliability in revealing intricate diplomatic dynamics.
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