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系統識別號 U0026-1607201816251100
論文名稱(中文) 具永續概念之群眾募資提案與募資成效分析: 文字探勘之應用
論文名稱(英文) Proposal Presentation and Success Prediction of Crowdfunding with the Concept of Sustainability: Application of Text Mining
校院名稱 成功大學
系所名稱(中) 資源工程學系
系所名稱(英) Department of Resources Engineering
學年度 106
學期 2
出版年 107
研究生(中文) 莊鈞諺
研究生(英文) Jun-Yan Zhuang
電子信箱 ny8426@gmail.com
學號 N46051229
學位類別 碩士
語文別 中文
論文頁數 112頁
口試委員 指導教授-施勵行
口試委員-陳梁軒
口試委員-陳家豪
中文關鍵字 群眾募資  永續發展  文字探勘  LDA主題模型  LIWC詞類計算 
英文關鍵字 Crowdfunding  Sustainable Development  Text Mining  Latent Dirichlet Allocation  Linguistic Inquiry and Word Count 
學科別分類
中文摘要 群眾募資(Crowdfunding)是大眾捐助創新者的重要途徑,也可以看出社會對創新的看法。因此,藉由研究永續發展相關議題在群眾募資的募資表現可以探討永續創新在台灣社會的接納程度。本研究藉由中文的群眾募資網站flyingV上的所有提案進行研究,分析頁面上提案者提供的提案介紹資料,並透過兩種文字探勘的技術抽取文字特徵: (1)應用隱含狄利克雷分配(Latent Dirichlet Allocation, LDA)主題模型方法進行主題分析,找出了募資平台上26個不同的主題,其中永續發展目標相關的10個主題,並將提案的文字資料以主題分配(Topic distribution)的形式量化;(2)語文探索與字詞計算(Linguistic Inquiry and Word Count,LIWC)從提案敘述文字中提取與心理、語言相關的敘事策略之特徵--LIWC詞類百分比。接著,基於提案的主題分配將提案進行階層式聚類分析(Hierarchical clustering),而從分群的結果發現提案基於其回饋品的用途可分成產品導向募資與行動導向募資兩類。最後,將募資目標金額、募資時間長短、提供回饋方案選樣數目、字數、主題分布與LIWC詞類百分比作為變數,分別對兩個導向募資的變數進行逐步變數篩選(Stepwise selection),選出與影響募資成敗的變數,並建立邏輯斯回歸(Logistic regression)模式預測募資成功率,迴歸結果顯示產品導向中並沒有任何永續議題的出現對募資有顯著的正向影響,而在行動導向募資中「動物保護」與「教育」主題出現募資具有正向的影響,另外 LIWC變數的結果顯示兩種導向中,說服語言使用策略上的差異,最後本研究使用資料集外的募資提案資料驗證本研究可以預測中文群眾募資提案的成功率。
英文摘要 Crowdfunding shows the society's perception of the innovation. Therefore, by studying the performance of crowdfunding related to the issues of sustainable development, we can explore the acceptance of sustainable innovation in the Taiwan society.
This study is based on the proposals on a Chinese crowdfunding platform. We analyze the proposal materials provided by the proposers, and extract text features through two text mining techniques. First, Latent Dirichlet Allocation (LDA) topic model was used to analyze the topics, it identifies 26 different topics on the crowdfunding platform, including 10 topics related to the sustainable development goals. The output of LDA model was also used to cluster the crowdfunding proposals. On the other hand, Linguistic Inquiry and Word Count (LIWC) extracted the features of narrative strategies from psychology and language dimension from the description of the proposals. And then, according to the clustering result, the proposals can be grouped into product-oriented crowdfunding and action-oriented crowdfunding based on the use of the feedback product. Finally, the basic information and text features of two groups of proposals were used as variables to perform stepwise selection and establish two Logistic regression models. The results show that no sustainable topic has significant positive impact on crowdfunding campaign in the product-orientation. In the action-oriented crowdfunding, the "Animal protection" and "Education" topics have positive impact. In addition, the LIWC variables show differences in persuading language strategies between the two orientations. The proposals outside the data set were used to verify the process in this study.
論文目次 摘要 II
Extend Abstract III
致謝 VI
目錄 VII
表目錄 X
圖目錄 XII
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 3
1.3 研究架構 4
第二章 文獻回顧 6
2.1 永續概念的群眾募資 6
2.2 永續群眾募資與一般商業募資提案中的語言差異 10
2.3 文字探勘 11
2.3.1 LIWC字詞計算 13
2.3.2 LDA主題模型 15
2.4 文件分群 17
2.5 基於文字特徵的預測 19
第三章 研究架構與方法 21
3.1 研究架構 21
3.1.1 研究範圍 21
3.1.2 研究流程 22
3.2 資料收集與預處理 25
3.2.1 資料收集階段 25
3.2.2 資料預處理階段 29
3.3 文字特徵抽取 31
3.3.1 LDA主題模型 31
3.3.2 LIWC詞類計算 36
3.4 提案分群 37
3.5 迴歸模型 39
3.5.1 變數篩選與解釋模型 41
3.6 實作預測 42
第四章 研究結果 44
4.1 主題模型結果 44
4.1.1 主題分析 44
4.1.2 永續概念主題 48
4.2 提案分群結果 50
4.2.1提案分群 50
4.2.2 產品與行動導向的募資 53
4.3 邏輯斯迴歸 53
4.3.1 逐步篩選 53
4.3.2 迴歸結果 55
4.4 實作預測結果 68
4.5 小結 70
第五章 結論與建議 71
參考文獻 73
附錄A 83
附錄B 88
附錄C 100
附錄D 104
附錄E 107
附錄F 110
附錄G 111
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網頁部分
1. 聯合國永續發展知識平台(2015),永續發展目標(SDGs)。取自:
https://sustainabledevelopment.un.org/sdg17
(造訪時間:2018.05.25)
2. Qin Wenfeng & Wu Yanyi (2018),R語言套件Package ‘jiebaR’使用手冊。取自:
https://cran.r-project.org/web/packages/jiebaR/jiebaR.pdf
(造訪時間:2018.05.29)
3. 維基百科(2018),LDA模型式意圖。取自:
https://en.wikipedia.org/wiki/File:Smoothed_LDA.png
(造訪時間:2018.05.24)
4. flyingV官方網站(2018),flyingV介紹取自:
https://www.flyingv.cc/about
(造訪時間:2018.05.29)
5. Feinerer I . Package ‘tm’(2017),R語言套件tm說明。取自:
https://cran.r-project.org/web/packages/tm/tm.pdf.
(造訪時間:2018.05.25)
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