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博碩士論文 etd-0113117-150008 詳細資訊
Title page for etd-0113117-150008
論文名稱
Title
文本作品的情緒探勘
A Study of Emotional Text Mining
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
70
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2017-01-23
繳交日期
Date of Submission
2017-02-13
關鍵字
Keywords
文字探勘、情緒分析、潛在語意分析、自然語言處理
Sentiment Analysis, Text Mining, Natural Language Processing, Latent Semantic Analysis
統計
Statistics
本論文已被瀏覽 5957 次,被下載 598
The thesis/dissertation has been browsed 5957 times, has been downloaded 598 times.
中文摘要
在各式各樣的小說當中,隨著內容文字的變化,讀者的情緒也常常隨之起伏。而隨著每個作者用字遣詞習慣的不同,也會形成獨特的寫作風格,有些甚至會成為其他人爭相模仿的對象,進而形成引領當代作品的潮流等。而在這些小說當中,去除劇情的影響力外,作家使用的情緒字詞數量、頻率或是強烈程度等會連帶影響每個讀者閱讀該小說時情緒的起伏。對於作者來說,傳統文學小說在只有文字為媒介的情況下,如何操作所使用的不同字彙來牽引讀者情緒,進而找出暢銷作品的獨特套路,或是不同類型的作品可能使用的情緒引領手法也不太相同。
因此在本篇論文中,試著利用英國作查爾斯‧狄更斯的作品《遠大前程》作為分析之文本,以Plutchik的八個情緒作為基礎情緒進行計算,能夠比單純以正負項數值更準確地表達情緒的變化,而在使用文法規則加以規範,以章節為單位觀察文本作品的情緒流向變化,來了解使用情緒字詞數量、頻率或是強烈程度等所帶來的閱讀情緒起伏影響。
Abstract
Readers who touched by the texts in various novels always exhibit mood swings. The choice of words made by different authors makes the writing style of the article unique. Some of the authors may even become a role model leading the contemporary trend. However, the amount of emotional words, its usage frequency and intensity may also affect every reader’s mind regardless of the plot. As for an author, there’s slightly difference between various types of literature for how to touch readers and make their piece of work a best-selling book.
Therefore, we are trying to analysis Charles Dickens’ fiction《Great Expectations》 for understanding the influence of emotional words, its usage frequency and intensity for readers based on calculating Plutchik’s eight basic emotions with grammar and observing the change of emotion flow in chapter, which is much precise on explaining emotional changes than simple calculation with positive and negative scores.
目次 Table of Contents
論文審定書 i
摘要 ii
ABSTRACT iii
目錄 iv
圖目錄 vii
表目錄 viii
1 緒論 1
1.1 研究背景與動機 1
1.2 研究問題 3
2 文獻探討 5
2.1 理論概念 5
2.1.1 Wheel of Emotion 5
2.1.2 Pointwise Mutual Information (PMI) 6
2.1.3 Sequence Alignment 6
2.2 情緒定義 7
2.3 情緒辨識技術的演進 8
2.4.1 情緒極性與類別法 Categorical Model 9
2.4.2 維度座標法 Dimensional Model 10
2.4 相似之情緒分析服務 11
2.5 潛在語意分析 Latent Semantic Analysis 15
3 研究方法 17
3.1 研究問題定義 17
3.1.1 情緒的分類方式與表達 17
3.1.2 各時代小說類型梗概 19
3.1.3 分析文本介紹 20
3.2 流程架構 20
3.3 字詞字句分析 21
3.3.1 情緒辭典Emotion Dictionary 21
3.3.2 Sentence-Level分析 23
3.4 語意分析 27
3.4.1 Latent Semantic Analysis (LSA) 27
3.5 作家寫作風格相似性計算 31
4 實驗與成果 32
4.1 情緒辨識方法準確度測量探討 32
4.1.1 實驗流程 32
4.1.2 實驗問卷 34
4.1.3 資料分析與整理 34
4.1.4 實驗組與對照組比較 35
4.1.5 精確度與準確度評估 37
4.2 作家寫作風格變化探討 46
4.3 實驗成果探討 52
4.3.1 實驗結果分析 52
4.3.2 導致實驗誤差的因素 54
5 結論 56
5.1 總結 56
5.2 研究限制 56
5.2.1 實驗受測者限制 56
5.2.2 系統限制 56
5.2.3 實驗章節限制 57
5.3 研究貢獻 57
5.4 未來展望 58
參考文獻 59
參考文獻 References
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