Using Semantic Analysis Tools to Explore the Media Framework and Impacts of Archival-Themed News during Taiwan’s Presidential Elections

Archives serve as critical evidence in documenting national development and are frequently employed by the media as a foundation for political discourse, particularly when addressing significant political issues. During election periods, the media often utilize archival-related news to reinterpret historical events, influencing public collective memory and shaping perceptions of national identity. This study applies text mining techniques to examine 534 news articles related to archival issues published by three major Taiwanese newspapers—United Daily News, Liberty Times, and China Times—during six presidential elections between 2000 and 2020. By employing Jieba, CKIP Tagger, and LDA models, the research analyzes reporting frequency, keyword frequency, and TF-IDF values, while also conducting topic clustering on the news content. The findings reveal that during election periods, archival-related news frequently highlights key terms such as “archive,” “history,” “government,” and “president,” with central figures consistently featured, including Chiang Kai-shek, Chiang Ching-kuo, and Lee Teng-hui. Furthermore, the topic clustering results indicate that the reporting framework of these archival news pieces primarily focuses on Taiwan’s first political party transition between 1999 and 2000 and is closely tied to debates concerning the “One China” policy.