社會公益群眾募資平台專案之 成功因素與文字採礦分析

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：89

、訪客IP：18.118.253.171

姓名

呂驊文(Hua-Wen Lu) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

社會公益群眾募資平台專案之成功因素與文字採礦分析
(The Successful Factors and Text Mining of Charitable Crowdfunding Projects)

相關論文

★ 美國軟體產業創新活動與財務效率分析	★ Performance Measurements of Web 2.0, Social Media, and Mobile Apps for Municipal Emergency Management
★ 中國大陸股權結構與自願性財務預測之關聯性	★ 我國半導體產業下游公司法人說明會對供應鏈上游公司投資現金流量敏感度的影響
★ 線上串流音樂服務之使用者抗拒意圖研究	★ 從認知理論探討創業機會辨識對績效之影響
★ 影響Y世代消費者對智慧綠色產品購買意圖與使用意圖的因素：以智慧節能裝置為例	★ Application of social media mining on the comparison between two-dimensional barcode and near field communication
★ 應用社群探勘技術分析城市之創業精神與新創公司的特性	★ 科技接受度與學習風格對於頭戴式虛擬實境應用在學習行為意圖的影響
★ 電子發票巨量資料視覺化分析－以酒的消費為例	★ 應用文字探勘分析ERP之趨勢發展：以Twitter為例
★ 社群媒體文字採礦之研究：以第三方物流公司為例	★ 應用文字探勘技術分析遊戲產業趨勢：以兩大遊戲展之相關推文為例
★ 台灣有機食品消費與疾病死亡率之視覺化分析	★ 酒類消費與犯罪率之視覺化分析

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

近年來，公益型群眾募資逐漸受到關注，公益團體擺脫過去「盲捐」方式，利用網路以及群眾募資平台大幅提高公益活動之曝光度，成為現今公益團體最主要的募資管道之一。本研究收集了公益群眾募資平台2015年9月至2020年3月之募資專案計畫，採用羅吉斯迴歸、文字採礦以及情緒分析，探討公益型專案募資之成功因素與文字採礦分析。本研究之變數聚焦於「專案內容」、「募資金額」、「回饋方案」與「專案更新與用戶參與」之面向。透過羅吉斯迴歸分析發現，「專案內容」與「專案更新與用戶參與」對於專案募資是否成功有顯著之正向影響。本研究進一步利用主題分析與情緒分析，將研究資料分為數個主題，探究何種公益議題較受到社會大眾之關注，並觀察各主題下專案計畫之情緒波動。研究結果發現，可將研究資料分為「老年議題」、「動物保育」、「環境保護」、「兒童教育」、「弱勢關懷」五個主題，其中「動物保育」以及「兒童教育」為最多人關注之社會公益議題。在情緒分析結果可發現，「環境保護」與「兒童教育」產生較多正向情緒波動，「動物保育」產生較多負向情緒。

摘要(英)

In recent years, charitable crowdfunding has gradually drawn attention. Nonprofit organization uses to apply the traditional method of donation in the past, and start using internet and crowdfunding platforms to highly increase the exposure of charitable ac-tivities, becoming one of the most important fundarising channels today. The research sample includes projects from charitable crowdfunding platform, for the period of Sep-tember 2015 to March 2020. This study focuses on four possible determinants: 1. pro-ject content, 2. fundraising, 3. reward, 4. user participation and project update. By using Logistic regression method, this study finds that project content, user participation and project update positively affect the funding results. This study further uses topic analy-sis and sentiment analysis to divide the research data into several themes, to find which charitable issues are more concerned by the public. To observe the emotion of projects under each theme, the results of the study finds that the research sample can be divided into five themes, which are “senior issues”, “animal conservation”, “environment pro-tection”, “child education” and “vulnerable care”. “Animal conservation” and “child education” are popular issues. From the results of sentiment analysis, the study can be found that “environmental protection” and “child education” produce more positive emotions, and "animal conservation" produce more negative emotions.

關鍵字(中)

★ 社會公益
★ 群眾募資
★ 文字採礦
★ 情緒分析
★ 主題分析

關鍵字(英)

★ charitable crowdfunding
★ text mining
★ topic analysis
★ sentiment analysis

論文目次

中文摘要...........................................................i
ABSTRACT..........................................................ii
第一章緒論.........................................................1
1-1 研究背景與動機...................................................1
1-2 研究目的 .......................................................3
第二章文獻探討......................................................5
2-1 社會公益群眾募資市場 .............................................5
2-2 募資專案計畫之成功因素............................................7
2-3 文字採礦與情緒分析...............................................10
第三章研究方法......................................................13
3-1 資料蒐集與變數說明................................................13
3-1-1 資料蒐集.......................................................13
3-1-2 變數說明.......................................................17
3-2 羅吉斯迴歸模型分析................................................19
3-3 主題分析 ........................................................21
3-4 情緒分析 ........................................................24
第四章研究結果與討論.................................................28
4-1 專案分析 ........................................................28
4-2 羅吉斯迴歸模型分析................................................31
4-3 主題分析 ........................................................34
4-4 情緒分析 ........................................................50
第五章結論..........................................................52
5-1 研究結論 ........................................................52
5-2 研究限制及未來研究方向............................................53
參考資料.............................................................55

參考文獻

Allahyari, M., Pouriyeh, S., Assefi, M., Safaei, S., Trippe, E. D., Gutierrez, J. B., & Kochut, K. (2017). A brief survey of text mining: Classification, clustering and extraction techniques. arXiv preprint arXiv:1707.02919.
Bagheri, A., Chitsazan, H., & Ebrahimi, A. (2019). Crowdfunding motivations: A focus on donors′ perspectives. Technological Forecasting and Social Change, 146, 218-232.
Chaplot, S. (2016). Reshaping Traditional Ways of Learning. The Internet of Women: Accelerating Culture Change.
Choy, K., & Schlagwein, D. (2016). Crowdsourcing for a better world. Information Technology & People, 29(1), 221.
Gerber, E. M., Hui, J. S., & Kuo, P.-Y. (2012). Crowdfunding: Why people are motivated to post and fund projects on crowdfunding platforms. Paper presented at the Proceedings of the international workshop on design, influence, and social technologies: techniques, impacts and ethics.
Gleasure, R., & Feller, J. (2016). Does heart or head rule donor behaviors in charitable crowdfunding markets? International Journal of Electronic Commerce, 20(4), 499-524.
Gorbatai, A., & Nelson, L. (2015). The narrative advantage: Gender and the language of crowdfunding. Haas School of Business UC Berkeley. Research Papers.
Hong, Y., Hu, Y., & Burtch, G. (2018). Embeddedness, pro-sociality, and social influence: Evidence from online crowdfunding. MIS Quarterly, Forthcoming.
Joenssen, D., Michaelis, A., & Müllerleile, T. (2014). A link to new product preannouncement: Success factors in crowdfunding. Available at SSRN 2476841.
Kleinbaum, D. G., Dietz, K., Gail, M., Klein, M., & Klein, M. (2002). Logistic regression: Springer.
Koch, J.-A., & Siering, M. (2015). Crowdfunding Success Factors: The Characteristics of Successfully Funded Projects on Crowdfunding Platforms.
Kuppuswamy, V., & Bayus, B. L. (2018). Crowdfunding creative ideas: The dynamics of project backers The economics of crowdfunding (pp. 151-182): Springer.
Liu, L., Suh, A., & Wagner, C. (2017). Donation behavior in online micro charities: An investigation of charitable crowdfunding projects. Paper presented at the Proceedings of the 50th Hawaii International Conference on System Sciences.
Lu, C.-T., Xie, S., Kong, X., & Yu, P. S. (2014). Inferring the impacts of social media on crowdfunding. Paper presented at the Proceedings of the 7th ACM international conference on Web search and data mining.
Mollick, E. (2014). The dynamics of crowdfunding: An exploratory study. Journal of business venturing, 29(1), 1-16.
Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2), 1-135.
Profatilov, D. A., Bykova, O. N., & Olkhovskaya, M. O. (2015). Crowdfunding: Online charity or a modern tool for innovative projects implementation? Asian Social Science, 11(3), 146.
Rhue, L., & Robert, L. P. (2018). Emotional delivery in pro-social crowdfunding success. Paper presented at the Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems.
56
Schwienbacher, A., & Larralde, B. (2010). Crowdfunding of small entrepreneurial ventures. Handbook of entrepreneurial finance, Oxford University Press, Forthcoming.
Vijayarani, S., Ilamathi, M. J., & Nithya, M. (2015). Preprocessing techniques for text mining-an overview. International Journal of Computer Science & Communication Networks, 5(1), 7-16.
Wang, N., Li, Q., Liang, H., Ye, T., & Ge, S. (2018). Understanding the importance of interaction between creators and backers in crowdfunding success. Electronic Commerce Research and Applications, 27, 106-117.
Wang, S.-M., & Ku, L.-W. (2016). ANTUSD: A large Chinese sentiment dictionary. Paper presented at the Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC′16).
Wang, W., Zhu, K., Wang, H., & Wu, Y.-C. J. (2017). The impact of sentiment orientations on successful crowdfunding campaigns through text analytics. IET Software, 11(5), 229-238.
Wash, R. (2013). The value of completing crowdfunding projects. Paper presented at the Seventh International AAAI Conference on Weblogs and Social Media.
Westerlund, M., Singh, I., Rajahonka, M., & Leminen, S. (2019). Can short-text project summaries predict funding success on crowdfunding platforms? Paper presented at the ISPIM Conference Proceedings.
Wu, H.-H., Tsai, A. C.-R., Tsai, R. T.-H., & Hsu, J. Y.-J. (2013). Building a Graded Chinese Sentiment Dictionary Based on Commonsense Knowledge for Sentiment Analysis of Song Lyrics. J. Inf. Sci. Eng., 29(4), 647-662.
Xu, A., Yang, X., Rao, H., Fu, W.-T., Huang, S.-W., & Bailey, B. P. (2014). Show me the money! An analysis of project updates during crowdfunding campaigns. Paper presented at the Proceedings of the SIGCHI conference on human factors in computing systems.
Yu, Y., Duan, W., & Cao, Q. (2013). The impact of social and conventional media on firm equity value: A sentiment analysis approach. Decision Support Systems, 55(4), 919-926.
Yuan, H., Lau, R. Y., & Xu, W. (2016). The determinants of crowdfunding success: A semantic text analytics approach. Decision Support Systems, 91, 67-76.

指導教授

沈建文(Chien-wen Shen)

審核日期

2020-7-21

推文