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International Area Studies Review

ISSN : 2233-8659 (Print)

‘Hybrid Open Access Journal
  • KCI(Korea Citation Index)
  • DOI(CrossRef)
  • DOI(CrossCheck)

International Area Studies Review

ISSN : 2233-8659 (Print)

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International Area Studies Review - Vol. 27 , No. 1
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[ Article ]
International Area Studies Review - Vol. 27, No. 1, pp. 43-56
Abbreviation: IASR
ISSN: 2233-8659 (Print)
Print publication date 31 Mar 2024
DOI: https://doi.org/10.69473/iasr.2024.27.1.43

Advanced Natural Language Processing Analysis on Cross-Border Media Sentiment from China and South Korea
Jinhyoung Kim ; Wonseong Kim
Hankuk University of Foreign Studies, HK+ National Strategies Research Project Agency
Korea University, Institute of Economics and Statistics

Correspondence to : Wonseong Kim, 145, Anam-ro, Seongbuk-gu, Seoul, Republic of Korea Email: wonseongkim@korea.ac.kr

Funding Information ▼
Abstract

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.

Keywords: China and Korea, International Economics, International Relations, Economic Methodology, Advanced Natural Language Processing (NLP), Sentiment Analysis
AI Acknowledgment

Generative AI or AI-assisted technologies were not used in any way to prepare, write, or complete essential authoring tasks in this manuscript.

Conflict of Interests

The author(s) declare that there is no conflict of interest.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A6A3A04064633).

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