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題名 Interpersonal Network Modeling Based on Text Analysis: A Case Study Using the Overseas Taiwanese Leftist Database
作者 廖文宏
Liao, Wen-Hung;Wu, Yi-Chieh;Hsueh, Hua-Yuan;Chang, Hui-Chen
貢獻者 資訊系
關鍵詞 Natural Language Processing; Deep Learning; Named Entity Recognition; Interpersonal Relationship Network; Data Visualization
日期 2025-01
上傳時間 19-May-2025 11:44:27 (UTC+8)
摘要 This paper draws on digital archives known as the “Taiwan Times Society” led by the leftist movement leader Tso Hsiung. The database contains magazines, internal newsletters, and correspondence among members published by the Taiwan Times Society from 1970 to 2018, totaling 498 documents with 2.29 million words. After digitization, we employed natural language processing techniques for named entity recognition (NER), keyword extraction, and the analysis of social network relationships among members. The results are dynamically presented through data visualization, creating comprehensive network graphs that encompass various aspects and relationships. Such visualizations serve as convenient tools to assist qualitative and quantitative research in social sciences and digital humanities field.
關聯 Proceedings of the 19th International Conference on Ubiquitous Information Management and Communication (IMCOM), IEEE SMC Society
資料類型 conference
DOI https://doi.org/10.1109/IMCOM64595.2025.10857495
dc.contributor 資訊系
dc.creator (作者) 廖文宏
dc.creator (作者) Liao, Wen-Hung;Wu, Yi-Chieh;Hsueh, Hua-Yuan;Chang, Hui-Chen
dc.date (日期) 2025-01
dc.date.accessioned 19-May-2025 11:44:27 (UTC+8)-
dc.date.available 19-May-2025 11:44:27 (UTC+8)-
dc.date.issued (上傳時間) 19-May-2025 11:44:27 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/157011-
dc.description.abstract (摘要) This paper draws on digital archives known as the “Taiwan Times Society” led by the leftist movement leader Tso Hsiung. The database contains magazines, internal newsletters, and correspondence among members published by the Taiwan Times Society from 1970 to 2018, totaling 498 documents with 2.29 million words. After digitization, we employed natural language processing techniques for named entity recognition (NER), keyword extraction, and the analysis of social network relationships among members. The results are dynamically presented through data visualization, creating comprehensive network graphs that encompass various aspects and relationships. Such visualizations serve as convenient tools to assist qualitative and quantitative research in social sciences and digital humanities field.
dc.format.extent 112 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Proceedings of the 19th International Conference on Ubiquitous Information Management and Communication (IMCOM), IEEE SMC Society
dc.subject (關鍵詞) Natural Language Processing; Deep Learning; Named Entity Recognition; Interpersonal Relationship Network; Data Visualization
dc.title (題名) Interpersonal Network Modeling Based on Text Analysis: A Case Study Using the Overseas Taiwanese Leftist Database
dc.type (資料類型) conference
dc.identifier.doi (DOI) 10.1109/IMCOM64595.2025.10857495
dc.doi.uri (DOI) https://doi.org/10.1109/IMCOM64595.2025.10857495