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| Title: | 古籍數位人文研究平台之史料人物關係圖工具發展與應用-以明代文集之人物為例
Development and Application of Ancient Books Digital Humanities Research Platform with Characters’ Relationship Map - A Case Study of the Characters in the Ming Dynasty Ancient Books |
| Authors: | 張鐘
Chang, Chung |
| Contributors: | 陳志銘
Chen, Chin-Ming
張鐘
Chang, Chung |
| Keywords: | 數位人文
社會網絡分析
人機互動
文本探勘
資訊視覺化
Digital humanities
Social network analysis
Human–computer interaction
Text mining
Data visualization |
| Date: | 2018 |
| Issue Date: | 2018-08-06 18:11:13 (UTC+8) |
| Abstract: | 本研究旨在開發支援數位人文研究之「古籍數位人文研究平台之史料人物關係圖」，能自動識別文本中的人名，同時提供易上手的即時互動介面，透過人機互動方式協助人文學者更有效率且正確的建立擬分析文本之人物社會關係，以探索複雜的人物社會網絡關係，找到有用的研究發現。本研究以實驗研究法比較有無使用本研究發展之「史料人物關係圖系統」在支援人文學者解讀文本中的人物與人物關係成效，以及科技接受度是否具有顯著差異，並輔以半結構式深度訪談了解人文學者對於本研究發展之「史料人物關係圖」的看法與感受，也使用滯後序列分析析受測者使用「史料人物關係圖」解讀人物與人物關係的行為歷程，以及解讀人物與人物成效及關係，與受測者使用「史料人物關係圖」系統的行為歷程之間是否具有顯著關聯性。
實驗結果發現，採用本研究發展之史料人物關係圖系統，在解讀人物與人物關係成效上高於使用無史料人物關係圖的系統，但未達顯著差異；採用史料人物關係圖系統的技接受度顯著高於無史料人物關係圖的系統。而相關分析部分，使用「史料人物關係圖」系統解讀文本中的人物成效與解讀文本中的人物關係成效之間達顯著正相關，但與使用者行為歷程之間無顯著關聯性。由訪談結果歸納得知，受訪者對系統介面的整合與操作的流暢度給予正面的評價；史料人物關係圖部分，多數受訪者認為史料人物關係圖能方便他們了解整體文本中的人物脈絡，但人名辨識的準確性仍有待改善。未來將利用機器學習方法，建立明代文集人名的實體命名辨識模型，以及提供社會網絡相關測度，讓系統更加完善，提高輔助人文學者解讀人物與人物關係的效益。
This research aims to develop the Books Digital Humanities Research Platform with Characters’ Relationship Map, which is able to identify the characters from the ancient books automatically. It also provides the user-friendly interface and helps humanities scholars to interpret characters’ relationship more efficiently and accurately by way of Human-Computer Interaction. Humanities scholars can discover the characters’ complex social network through the Characters’ Relationship Map to obtain useful findings.
With experimental method, the research compared the outcomes with and without the Characters’ Relationship Map assisting humanities scholars to interpret the character and the characters’ relationship in the ancient books, and if there were significant differences in technology acceptance. Via semi-structured in-depth interviews, the research acquired humanities scholars’ opinions and perception about the Characters’ Relationship Map. The research utilized lag sequence analysis to analyze users’ behavior processes and achievements of using Characters’ Relationship Map as well as investigating the correlations between users’ behavior processes and achievements.
The experimental results show that the system with the Characters’ Relationship Map is higher than the system without the Characters’ Relationship Map in both the interpretation of the character and the interpretation of the characters’ relationship, but not significant. The technology acceptance analysis reveals that the system with the Characters’ Relationship Map has significantly better technology acceptance than the system without the Characters’ Relationship Map. There is significant correlation between the achievements of interpreting the character and the characters’ relationship, but no significant correlation among users’ behavior processes. According to the interviews, respondents gave positive comments on the integration and operational fluency of the system interface. Many respondents believed that the Characters’ Relationship Map could help them better understand the context of the characters in the overall text, but the accuracy of the identification of names still needs to be improved.
In the future, we will use machine learning to establish name entity model for Ming Dynasty and also provide social network related measures to make the system more perfect so as to raise the benefits of assisting humanities scholars to interpret characters and characters’ relationship. |
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| Description: | 碩士
國立政治大學
圖書資訊與檔案學研究所
105155004 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0105155004 |
| Data Type: | thesis |
| DOI: | 10.6814/THE.NCCU.LIAS.009.2018.A01 |
| Appears in Collections: | [圖書資訊與檔案學研究所] 學位論文
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