Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/132458
題名: 社群聊天機器人互動率探究與使用者行為分析
Investigation of Engagement Rate and Analysis of User Behavior for Chatbots on Social Media
作者: 馬翊
Ma, Yi
貢獻者: 陳聖智<br>廖峻鋒
Chen, Sheng-Chih<br>Liao, Chun-Feng
馬翊
Ma, Yi
關鍵詞: 社群聊天機器人
互動率
使用者行為
使用者體驗
科技接受模型
Chatbots on social media
Engagement rate
User behavior
User experience
Technology acceptance model
日期: 2020
上傳時間: 3-十一月-2020
摘要: 聊天機器人的概念發展至今已有七十年的歷程,隨著使用者的使用習慣轉變及行動裝置蓬勃發展,結合社群媒體之社群聊天機器人也日漸活絡,發展出各式各樣的應用情境,不但使對話式商務興起,更讓使用者與聊天機器人的距離越來越近,而社群聊天機器人即時且容易操作的特性,也被運用於社群媒體之客服服務或娛樂及遊戲服務上。在現今與社群媒體密不可分的世代,互動率及互動體驗更是成為一大評估社群媒體成效的重要指標,也因此開始有經營者將社群聊天機器人導入社群媒體中,藉由社群聊天機器人的力量提升社群媒體之互動率。\n\n在各式各樣的應用中,娛樂及遊戲型社群聊天機器人已有提升社群媒體互動率之實,但卻缺乏相關研究文獻以了解背後之歸因,而在進行服務流程及使用體驗優化時也缺乏相關依據。因此,本研究在進行互動率探究之外,也納入其他互動相關概念,與三位社群專家進行半結構式訪談,並搜集、觀察、整理實際一社群聊天機器人相關之數據指標為基礎,針對娛樂及遊戲型社群聊天機器人進行互動率之探討;也利用問卷調查法搜集346份問卷,以人機互動量表檢視使用者的互動感知程度和與再互動意願之間的關係;並實際製作社群聊天機器人貼文,與7位受測者進行測試、訪談與分析,以科技接受模型理論為基礎,探究使用者對於再互動之行為意向;除此之外,更透過與使用者的對話,實際繪製娛樂及遊戲型社群聊天機器人之使用者旅程地圖,以此作為服務及使用體驗優化之基礎。\n\n研究結果發現,娛樂及遊戲型社群聊天機器人可為品牌及其粉絲專頁帶來正向影響;「娛樂感」與「感知挑戰」為使用者決定是否進行再互動之考慮因素;另外,若能在滿足認知易用性及認知有趣性後,再額外滿足認知有用性,將能夠在使用者心中留下深刻印象,發揮價值作為使用者的社交資本;而在使用者類型分眾上,可分為連結共鳴型、自我滿足型、理性評估型、社交目的型等四種類型;在服務流程上,最需要改進的部分在留言回覆、同意GDPR、再互動意願、下次推播再互動等階段,應思考如何降低使用者的未知焦慮。
The concept of chatbot can be traced back to 70 years ago. With user habits changing and mobile devices establishing, chatbot designed for social media applications is now flourishing, with multiple functions being developed for various scenarios. Chatbot commerce is a rising business as users’ willingness to engage with chatbot increases. Chatbot’s accessibility and immediacy have been widely utilized in customer service for social media and entertainment purposes. As social media becomes a crucial part of our day-to-day life, engagement and interactivity are deemed vital when evaluating social media performances. Hence, chatbot is now utilized in social media operation as a means of optimizing interactivity with users.\n\nAmong the various applications, chatbot for entertainment and gaming purposes have shown results in optimizing user interactivity. However, there is a lack of related research to analyze the causes behind such outcomes. References are also hard to acquire when utilizing chatbot or optimizing the user experience. The purpose of this study was to research the engagement of chatbot services. Other interactive concepts were also utilized in the study as well. Semi-structured interviews were conducted with three social media operators to gather and monitor the data, specifically focusing the engagement rate from chatbots used for entertainment and gaming purposes. 346 questionnaires were also collected, detailing surveyors’ human-computer interaction experience and their willingness to repeat the interactions. Chatbot experience were recreated for seven testees for interview and analytical purposes, using Technology Acceptance Model to analyze users’ willingness to repeat the chatbot experience. Furthermore, user journey maps were developed to exemplify their experiences with chatbots for further optimization purposes.\n\nThe study indicated that chatbots for entertainment and gaming purposes can bring positive influence for brands and fan pages, while “entertainment” and “perceived task challenge” are considered determining factors for users to repeat the experience. In addition to sustaining users ’perceived ease of use and perceived enjoyment, perceived usefulness can enhance the experience and further the service as a social capital for the users. Four categories can be sorted based on the users’ demographic: relatability, satisfaction, rationality and sociability. In service produces, findings suggested that the parts that require the most improvement are the reply messages, GDPR agreement, willingness for repeated interaction and willingness to replicate actions when receiving further notification. The study also indicated that minimizing users’ anxiety when engaging with unknown service is crucial for optimizing chatbot experience.
參考文獻: 中文部分\n\n王凱、王存國、范錚強(2006)。線上環境中廣告情境呈現與執行手法對廣告效果的影響:廣告變化、訊息訴求與導引效果。資訊管理學報,13(3),1-28。\n池熙璿(譯)(2013)。這就是服務設計思考!(原作者:Marc Stickdorn、Jakob Schneider, 2011)。台北市:中國生產力中心。\n何舒軒、宋同正 (2014)。綜論服務設計學術研究發展。設計學報,19(2),53-74。\n宋同正 (2014)。序-服務設計的本質內涵和流程工具。設計學報,19(2),1-8。\n邱皓政(2020)。量化研究法(二):統計原理與分析技術 二版。台北市:雙葉。\n洪雪珍(2017)。為何聽算命、星座分析,都覺得超準?心理學家大公開:全球命理師都用「這一招」鐵口直斷。上網日期:2020 年 2 月 5 日。檢自:https://www.storm.mg/lifestyle/377724\n耿慶瑞(1999)。WWW互動廣告效果之研究。國立政治大學企業管理學系博士論文。臺北市。\n耿慶瑞(2000)。互動廣告之互動層次。廣告學研究,15,161-181。\n高敬原(2017)。小編注意!Facebook上濫用「讚」、「tag人」、「分享」將被懲罰降低觸及。上網日期:2020 年 2 月 5 日。檢自:https://www.bnext.com.tw/article/47490/facebook-fights-engagement-baiting-spam-in-your-news-feed\n張偉男、劉挺(2016)。〈聊天機器人技術的研究進展〉。《中國人工智慧學會通訊》,6(1),17-21。\n曹瀞云(2019)。台灣民法智能聊天機器人助理之研究與開發。實踐大學資訊科技與管理學系碩士班碩士論文。台北市。\n許維娟(2017)。人機互動傳播科技影響置入行銷購買意願之研究。中華印刷科技年報,372-402。\n陳奕君(2020)。台灣投資人對於機器人理財行為意圖之研究。政治大學國際經營與貿易學系學位論文。台北市。\n陳彥妤(2018)。探討聊天機器人的信任轉移及對使用者網路再購意圖之影響。國立中山大學資訊管理學系碩士班碩士論文。高雄市。\n陳英華(2020)。以科技接受模型探討台灣與泰國外送平台的購買意願。國立臺北教育大學東南亞區域管理碩士學位學程學位論文。台北市。\n創市際市場研究顧問(2018)。〈2018台灣網路報告〉。財團法人台灣網路資訊中心。上網日期:2019年12月14日。檢自:https://report.twnic.tw/2018/#generalCards\n喬宗凡(2012)。Facebook粉絲專頁社會互動形式與社會資本對知覺品牌關係品質之影響研究。世新大學公共關係暨廣告學研究所(含碩專班)碩士論文。臺北市。\n彭昱傑(2017)。聊天機器人系統設計與實作。國立中正大學資訊工程研究所碩士論文。嘉義縣。\n曾曉彤(2018)。臉書社群廣告效果研究 : Chatbot與貼文廣告效果之比較。國立政治大學傳播學院傳播碩士學位學程碩士論文。台北市。\n黃珮茹(2017)。對話式商務-探討聊天機器人使用情境如何影響使用意願。國立清華大學服務科學研究所碩士論文。新竹市。\n黃健芳(2019)。〈《FB演算法專題》小編必看!臉書演算法進化史 粉絲團操作「不能說的秘密」〉。上網日期:2020 年 2 月 5 日。檢自:http://www.limedia.tw/comm/4955/\n黃朝秋、賴薇如(譯)(2018)。設計聊天機器人:建立對話式體驗(原作者:A. Shevat, 2018)。台北市:碁峰資訊。\n黃聖峯、鄒仁淳、林娟娟(2014)。社群網站之使用行為研究-以 Facebook 為例。Electronic Commerce Studies,12(2),201-234。\n董維、張瑞觀、梁榮達(2009)周邊路徑效果探討特定網路廣告態度形成:人機互動、情緒及一般網路廣告態度。電子商務學報,11(1),143-172。\n董維(2008)。探討消費者涉入程度與人機互動結果對特定廣告態度之影響。管理實務與理論研究,2(1),1-19。\n廖紫柔、張務華、羅居鎮(2020)。網站知名度與網站忠誠度之相關分析-以科技接受模式為中介變數。管理資訊計算,9(1),15-26。\n趙慧芬、吳莉君、林潔盈(譯)(2012)。設計的方法(原作者:Bella Martin、Bruce Hanington)。台北市:原點(原著作出版年:2012)。\n劉容之(2019)。聊天機器人應用於訂餐平台系統之建置與研究。國立屏東大學資訊科學系碩士班碩士論文。屏東縣。\n劉惠琴(2017)。〈Facebook Messenger 聊天機器人全球興起!每月活躍數破十萬〉。上網日期:2019 年 11 月 3 日。檢自 https://3c.ltn.com.tw/news/32165\n蔡佩珊(2019)。建置自動化客服回覆機制之聊天機器人。國立臺北科技大學工業工程與管理系碩士論文。台北市。\n鄭雲珊、許秉瑜、劉育津 (2014) 社群網站使用者個人價值與需求之探究。 Electronic Commerce Studies,12(1),51-72。\n顏理謙(2016)。Yahoo TV正式開台!強打自製網路直播節目。上網日期:2020 年 2 月 8 日。檢自:https://www.bnext.com.tw/article/40548/BN-2016-08-09-182652-42\nCHATISFY(2019)。小編必修課:如何利用行為科學提升轉換率。上網日期:2020 年 2 月 5 日。檢自:https://blog.chatisfy.com/how-to-use-behavioral-science-to-boost-your-fanpage/\nEILIS智慧互動助理(2018)。【聊天機器人】互動為王的新時代。上網日期:2019年11月2日。檢自:https://blog.eilis-ai.com/%E4%BA%92%E5%8B%95%E7%82%BA%E7%8E%8B%E7%9A%84%E6%96%B0%E6%99%82%E4%BB%A3-%E8%81%8A%E5%A4%A9%E6%A9%9F%E5%99%A8%E4%BA%BA%E7%82%BA%E4%BD%A0%E6%89%93%E9%80%A0%E6%99%BA%E6%85%A7%E4%BA%92%E5%8B%95-eadf83bce054\nGoSky(2019)。〈日韓旅遊挑戰賽!台灣雪豹科技公司,透過冷知識小遊戲讓用戶了解AI翻譯棒 | GoSky 數位新鮮人計畫〉。上網日期:2019年12月21日。檢自:https://www.goskyai.com/tw/blog/casestudy/leopard-mobile/\ni-Buzz 網路口碑研究中心(2017)。〈Facebook、Twitter、 Instagram,三大社群互動率的基本概念及計算方法〉。上網日期:2019 年 9 月 29 日。檢自 https://blog.dcplus.com.tw/marketing- knowledge/social_marketing/124036\nLINE TAXI(2017)。LINE TAXI官方網頁介紹。上網日期:2019年12月21日。檢自:https://linetaxi.com.tw/about/\nLINE(2017)。〈【功能介紹】Messaging API〉。上網日期:2019年12月21日。檢自:http://at-blog.line.me/tw/messaging_api_intro\nTC Sharing(2018)。聊天機器人(Chatbot)的發展歷程及趨勢?一 次讓你了解聊天機器人(Chatbot)概況。上網日期:2019年10月5日。檢自:https://sharing.tcincubator.com/%E8%81%8A%E5%A4%A9%E6%A9%9F%E5%99%A8%E4%BA%BAchatbot%E7%9A%84%E7%99%BC%E5%B1%95%E6%AD%B7%E7%A8%8B%E5%8F%8A%E8%B6%A8%E5%8B%A2%EF%BC%9F%E4%B8%80-%E6%AC%A1%E8%AE%93%E4%BD%A0%E4%BA%86%E8%A7%A3%E8%81%8A/\nUX實驗室(2017)。第一次畫使用者旅程圖 User Journey Map 就上手。上網日期:2020年1月21日。檢自:http://ux.pixnet.net/blog/post/324635842-%E7%AC%AC%E4%B8%80%E6%AC%A1%E7%95%AB%E4%BD%BF%E7%94%A8%E8%80%85%E6%97%85%E7%A8%8B%E5%9C%96-user-journey-map-%E5%B0%B1%E4%B8%8A%E6%89%8B\n\n英文部分\nAhn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263-275.\nAlbert, W., & Tullis, T. (2013). Measuring the user experience: collecting, analyzing, and presenting usability metrics. Newnes.\nBarnett, L. (1990). Playfulness: Definition, design, and measurement. Play & Culture, 3, 319-336.\nBasak, S. K., Govender, D. W., & Govender, I. (2016). Examining the impact of privacy, security, and trust on the TAM and TTF models for e-commerce consumers: A pilot study. In 2016 14th Annual Conference on Privacy, Security and Trust (PST) (pp. 19-26). IEEE.\nBuzzsumo (2019). The 2019 Ultimate Guide to Facebook Engagement. Retrieved from https://buzzsumo.com/blog/facebook-engagement-guide/ (2019/10/11)\nCarbone, M. (2016). Remembering SmarterChild. Retrieved from: https://blog.talla.com/remembering-smarterchild (2019/10/20)\nChefitz, M., Austin-Breneman, J., & Melville, N. (2018). Designing Conversational Interfaces to Reduce Dissonance. Paper presented at the Proceedings of the 2018 ACM Conference Companion Publication on Designing Interactive Systems, Hong Kong, China.\nCosima (2016). Conversational Interfaces: Where Are We Today? Where Are We Heading? Retrieved from: https://www.smashingmagazine.com/2016/07/conversational-interfaces-where-are-we-today-where-are-we-heading/ (2019/09/26)\nCsikszentmihalyi, M. (1988). Beyond Boredom and Anxiety: Jossey-Bass Publishers.\nDavis, F. (1986). A Technology Acceptance Model for Empirically Testing New End-User Information Systems. (Doctoral dissertation thesis)\nDavis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.\nDavis, F., Bagozzi, R., & Warshaw, P. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35, 982-1003.\nEadicicco L. (2015). Facebook Will Call Your Next Uber For You Retrieved from: https://time.com/4149291/facebook-messenger-uber/ (2019/11/14)\nEeuwen, M. V. (2017). Mobile conversational commerce: messenger chatbots as the next interface between businesses and consumers.\nFacebook (2019). Why Am I Seeing This? We Have an Answer for You. Facebook Newsroom. Retrieved from: https://about.fb.com/news/2019/03/why-am-i-seeing-this/ (2019/12/03)\nFishbein, M. & Ajzen, I. (1975). Beliefs, Attitude, Intention, and Behavior: An introduction to theory and research. Reading. Ma: Addison-Wesley.\nFlom, J. (2010). The value of customer journey maps: A UX designer’s personal Journey. Retrieved from:https://www.uxmatters.com/mt/archives/2011/09/the-value-of-customer-journey-maps-a-ux-designers-personal-journey.php (2019/11/22)\nFrantz, J. (2015). Updated controls for news feed. Facebook Newsroom. Retrieved from: http://newsroom.fb.com/news/2015/07/updated-controls-for-news-feed (2020/01/12)\nGalligan M. (2016). “Bot” is a hilariously over-simplified buzzword. Let’s fix that. Retrieved from:https://medium.com/@mg/bot-is-a-hilariously-over-simplified-buzzword-let-s-fix-that-f1d63abb8ba7#.8oja5u8w0 (2019/11/05)\nGhani, J., & Deshpande, S. (1993). Task Characteristics and the Experience of Optimal Flow in Human-Computer Interaction. The Journal of Psychology Interdisciplinary and Applied, 128, 381-391.\nHeeter, C. (1989). Implications of New Interactive Technologies for Conceptualizing Communication. Media Use in the Information Age: Emerging Patterns of Adoption and Consumer Use, 12, 217-235.\nHoffman, D. L., & Novak, T. P. (1996). Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations. Journal of Marketing, 60(3), 50-68.\nHu, T., Xu, A., Liu, Z., You, Q., Guo, Y., Sinha, V., Lou, J. &Akkiraju, R. (2018). Touch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media. Paper presented at the Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal QC, Canada.\nIgbaria, M., Schiffman, S. J., & Wieckowski, T. J. (1994). The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behaviour & Information Technology, 13(6), 349-361.\nIntercom (2016). 8 principles of bot design. Retrieved from:https://www.intercom.com/blog/?utm_medium=article&utm_source=medium&utm_campaign=botdesign (2019/10/02)\nJerry (2017). China, WeChat, and the Origins of Chatbots. Retrieved from: https://chatbotsmagazine.com/china-wechat-and-the-origins-of-chatbots-89c481f15a44 (2019/10/05)\nKacholia, V. (2013). News feed FYI: Showing more high quality content. Facebook Newsroom. Retrieved from: http://newsroom.fb.com/news/2013/08/news. feed.fyi.showing.more.high.quality.content (2020/01/08)\nKeil, M., Beranek, P. M., & Konsynski, B. R. (1995). Usefulness and ease of use: field study evidence regarding task considerations. Decision Support Systems, 13(1), 75-91.\nKlotzbach, C. (2017). Flurry State of Mobile 2017: With Captive Mobile Audiences, New App Growth Stagnates. Retrieved from: https://www.flurry.com/blog/tagged/insights (2019/12/08).\nLee, W., Xiong, L., & Hu, C. (2012). The effect of Facebook users’ arousal and valence on intention to go to the festival: Applying an extension of the technology acceptance model. International Journal of Hospitality Management, 31(3), 819-827.\nLempinen, K. (2017). What are Chatbots and how they impact Service Management. Retrieved from: https://lempinenpartners.com/what-are-chatbots-and-how-they-impact-service-management/ (2019/12/11).\nLieberman, J. N. (1977). Playfulness: Its Relationship to Imagination and Creativity: Academic Press.\nLin, C. S., Wu, S., & Tsai, R. J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information & Management, 42(5), 683-693.\nMager, B., & Sung, T. (2011). Special Issue Editorial: Designing for Services. International Journal of Design [Online] 5:2. Available: http://ijdesign.org/index.php/IJDesign/article/view/994 (2019/11/10).\nMalhotra, Y., & Galletta, D. F. (1999, 5-8 Jan. 1999). Extending the technology acceptance model to account for social influence: theoretical bases and empirical validation. Paper presented at the Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.\nMartin, B., Hanington, B., & Hanington, B. M. (2012). Universal Methods of Design: 100 Ways to Research Complex Problems, Develop Innovative Ideas, and Design Effective Solutions: Rockport Publishers.\nMassey, B. L., & Levy, M. R. (1999). Interactivity, Online Journalism, and English-Language Web Newspapers in Asia. Journalism & Mass Communication Quarterly, 76(1), 138-151.\nMcKenna, R. (1991). Relationship marketing : successful strategies for the age of the customer / Regis McKenna. Reading, Mass: Addison-Wesley Pub. Co.\nMcMillan, S. (2000). Interactivity is in the eye of the beholder: Function, perception, involvement, and attitude toward the web site. Proceedings of the 2000 Conference of the American Academy of Advertising, 71-78.\nMoon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.\nMoore, R. J., & Arar, R. (2018). Conversational UX Design: An Introduction. In Studies in Conversational UX Design (pp. 1-16).\nNielsen Norman Group (2018). The User Experience of Chatbots. Retrieved from:https://www.nngroup.com/articles/chatbots/ (2019/10/15).\nNishida, T. (2012). An Engineering Approach to Conversational Informatics, Berlin, Heidelberg.\nNovak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The Influence of Goal-Directed and Experiential Activities on Online Flow Experiences. Journal of Consumer Psychology, 13(1), 3-16.\nNovak, T., Hoffman, D., & Yung, Y.-F. (2000). Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Marketing Science, 19, 22-42.\nNunnally, J.C., (1978). Psychometric Theory, New York: McGraw-Hill.\nRafaeli, S., & Sudweeks, F. (1997). Networked Interactivity. Journal of Computer-Mediated Communication, 2(4). Retrieved from: https://academic.oup.com/jcmc/article/2/4/JCMC243/4584410 (2020/01/11).\nSchwier, R., & Misanchuk, E. (1993). Interactive multimedia instruction / Richard A. Schwier, Earl R. Misanchuk. Englewood Cliffs, N.J: Educational Technology Publications.\nShevat, A. (2017). Designing Bots: Creating Conversational Experiences: O`Reilly Media.\nStatisa (2019). Number of daily active Facebook users worldwide as of 3rd quarter 2019 (in millions) Retrieved from:https://www.statista.com/statistics/346167/facebook-global-dau/ (2020/02/15).\nStatisa (2019). Number of monthly active Facebook users worldwide as of 3rd quarter 2019 (in millions) Retrieved from:https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/ (2020/02/15).\nSteuer, J. (1992). Defining Virtual Reality: Dimensions Determining Telepresence. Journal of Communication, 73-93.\nStickdorn, M., Schneider, J., Andrews, K., & Lawrence, A. (2011). This is service design thinking: Basics, tools, cases (Vol. 1). Hoboken, NJ: Wiley.\nTse, A. C. B., & Chi-Fai, C. (2004). The Relationship between Interactive Functions and Website Ranking. Journal of Advertising Research, 44(4), 369-374.\nTuring, A. M. (1950). Computing machinery and intelligence. Mind, 59, 433-460.\nVrasidas, C., & McIsaac, M. S. (1999). Factors influencing interaction in an online course. American Journal of Distance Education, 13(3), 22-36.\nWeizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communication of the ACM, 9(1), 36-35\nXu, A., Liu, Z., Guo, Y., Sinha, V., & Akkiraju, R. (2017). A New Chatbot for Customer Service on Social Media. Paper presented at the Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, Colorado, USA.\nYockey, R.D. (2011). SPSS demystified-A step-by-step guide to successful data analysis for SPSS version 18.0 (2nd ed.). NY: Pearson.\nZue, V., & Glass, J. (2000). Conversational interfaces: advances and challenges. Proceedings Of The IEEE, 88(8), 1166-1180.
描述: 碩士
國立政治大學
數位內容碩士學位學程
107462006
資料來源: http://thesis.lib.nccu.edu.tw/record/#G0107462006
資料類型: thesis
Appears in Collections:學位論文
學位論文

Files in This Item:
File Description SizeFormat
200601.pdf7.64 MBAdobe PDF2View/Open
Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.