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  • 學位論文

中國古典白話小說中的社會網路關係:以《儒林外史》為例

Social Network Analysis in Classic Vernacular Chinese Novel: Take The Scholars as Example

指導教授 : 項潔

摘要


《儒林外史》是一部出現人物眾多、敘事結構相當獨特的白話寫實長篇章回小說,為中國諷刺文學的先聲。它雖然與《紅樓夢》同為清朝最著名的小說,但比起後者,《儒林外史》得到的注意似乎與其重要性不成正比,且缺乏在資訊領域方面的研究。而社會網絡分析雖已廣泛應用於許多研究領域,卻較少應用於文本分析之中。因此,我們想嘗試利用資訊技術建構並分析《儒林外史》的社會網絡,並回答與其有關的社會網絡議題。 在本研究中,我們發現《儒林外史》的全文有相當高比重的角色對話,而這是最重要的人物關係來源。因此,我們設計了一種半自動的方法,利用詞夾子演算法從全文中擷取資料,然後由角色對話建立並分析了《儒林外史》的社會網絡,且為其做了初步的文本分析。 在分析中,除了得知《儒林外史》的人物其所屬的團體以外,我們還發現了《儒林外史》一個較少人研究的角色──金東崖的重要性,並藉由各回中各角色說話內容的多寡得知了《儒林》中的確具有明顯的角色迭代結構。

並列摘要


The classic realistic vernacular novel “The Scholars” pioneered Chinese satire. It has a unique narrative style, in which there are hundreds of characters but none of them leads the story. It is the best-known novel during Qing Dynasty, just the same as “Dream of the Red Chamber”. However, the attention it acquires and the research been done on it are much less compared with the latter, and despite the extensive application of social network analysis, it is less applied to textual analysis. Therefore, we tried to use information technology to construct and analyze the social network of “The Scholars” and answered questions related to social network problems. In our research, we discovered that there is a high proportion of role dialogues in The Scholars, which is the most important source of role relations. Therefore, we designed a semi-automatic method to extract data from the full text of The Scholars using an algorithm called “word clipper”, and construct the social network based on the conversations of characters. After that, we did a preliminary textual analysis based on those quantitive data. During our analysis, besides finding out the community each role belongs, we discovered the importance of a little-researched character JIN Dong-ya, and learned the exact role-iterating status of The Scholars based on the talking of each characters.

參考文獻


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[33] 張尚斌,〈詞夾子演算法在專有名詞辨識上的應用:以歷史文件為例〉,臺灣大學資訊工程研究所碩士論文,2006年。
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被引用紀錄


黃家富(2017)。小說對話標註系統研究與實作〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU201701833

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