Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/130898
題名: 閱聽人與金融聊天機器人對話之接收分析 -以銀行場域為例
Reception Analysis of the Dialogue between the Audience and the Financial Chatbot - Take the Bank Scenario as an Example.
作者: 賴億華
Lai, Yi-Hua
貢獻者: 劉慧雯
Liu, Hui-Wen
賴億華
Lai, Yi-Hua
關鍵詞: 接收分析
閱聽人
金融聊天機器人
人機互動理論
Reception analysis
Audience
Financial chatbots
Human–computer interaction
日期: 2020
上傳時間: 3-Aug-2020
摘要: 科技賦能金融,帶動了金融科技3.0(Fintech 3.0)發展的熱潮。尤其是AI人工智慧及聊天機器人(chatbot)的應用,已成為不可逆的發展趨勢。以聊天機器人與人機互動過去的相關研究,多侷限於資訊技術的探討與使用性的趨勢了解,似乎忽略了使用者在真實使用情境是如何與機器人進行互動。互動對話過程中,使用者是在何種情境脈絡下接收機器人的對話,而這樣的情境脈絡是如何影響著使用者的解讀與詮釋,值得深入探討與研究,故引發了研究動機。\n\n因此,本研究從傳播學的觀點,使用者為閱聽人的角度、接收分析理論與閱聽人研究的取徑,並以銀行場域為例,探索閱聽人與聊天機器人的對話。透過文獻探討梳理、文本分析、觀察及深度訪談的質性研究,結果發現,閱聽人與聊天機器人對話,閱聽人所處的情境是透過對話介面,與聊天機器人一問一答的互動情境,呈現循環文本的模式。閱聽人對於對話的接收脈絡,則是以自身基本的金融常識與經驗造就了其識讀與理解,常以「換句話說」與「轉換關鍵字」的閱讀技能,來持續與機器人對話,並以主動閱聽人的身分,享有媒介近用權而主導對話的開啟與結束。\n\n閱聽人對於對話文本的接收解讀與詮釋,基於「好奇心」的驅使與「實用性的考量」作為對話內容的解讀策略,然而千禧世代與X世代受其背景經驗影響產生差異的解讀模式與詮釋,但僅體現於基金這類型的投資理財話題。對話後的詮釋,兩個世代的閱聽人都認為聊天機器人似乎只能解決簡單的問題,但閱聽人需要更即時互動的直覺式體驗,對話內容與閱聽人的生活經驗相連結,才能創造良好體驗。因此,期望研究結果能提供學術佐證與業界參考改善之依據。
Technology empowers finance, driving the upsurge in the development of Fintech 3.0. Especially the application of AI and chatbot has become an irreversible development trend. In the past, research related to the interaction between chatbots and human-machines was mostly limited to the discussion of information technology and the understanding of usability trends, and it seemed to ignore how users interact with machines in their actual usage scenarios. In the interaction process, under what context the user receives the dialogue of the robot, and how does this context affect the user`s interpretation and response, it is worth in-depth discussion and research, so it triggers research motivation.\n\nTherefore, In this research, from the perspective of communication studies, the user is from the perspective of the audience, reception analysis and the approach of the study of the audience, and taking the bank field as an example to explore the dialogue between the audience and the chatbot. Through the qualitative research of literature review, text analysis, observation and in-depth interviews, it was found that the audience and the chatbot are in the conversational user interface, and Interactive question-and-answer scenarios , Which presents a pattern of circulating text. The audience reception of dialogue are based on their basic financial knowledge and experience to create their reading and understanding. They often use the reading skills of "in other words" and "converting keywords" to talk with chatbot. And as the active readers, they have the right of access to the media and lead the opening and closing of the dialogue.\n\nThe audience interpretation and interpretation of the dialogue text is based on the drive of "curiosity" and "practical considerations" as the interpretation strategy of the dialogue content. However, the interpretation mode of the difference between Millennials and Generation X is affected by their background experience Interpretation, but only reflected in the investment and financial topics of the fund. Interpretation after the conversation, the two generations of audience think that chatbots can only solve simple problems, but they need a more instant interactive intuitive experience, and the dialogue can connect with the audience’s life experience to create a good experience. Therefore, it is expected that the research results can provide the basis for academic evidence and industry reference improvement.
參考文獻: 一、中文文獻\nAdobe(2019年8月27日)。《2019年數位趨勢報告》,取自Adobe網頁:https://www.adobe.com/content/dam/acom/uk/modal-offers/2019/DT-Report-2019/Econsultancy-2019-Digital-Trends-Financial-Services.pdf\nKPMG(2019年2月13日)。《2018年金融科技報告》,取自KPMG網頁:https://assets.kpmg/content/dam/kpmg/tw/pdf/2019/03/tw-kpmg-the-pulse-of-fintech-2018.pdf\nMaria Korolov、陳薇真(2018)。〈人工智慧改變客戶體驗的5種方式〉,《CIO IT經理人雜誌》,90: 76-79。\n王宜燕(2012)。〈閱聽人研究實踐轉向理論初探〉,《新聞學研究》,113: 39-75。\n王若樸(2018年8月18日)。〈如何跳脫傳統銀行包袱,台新打造貼心銀行靠AI四戰略〉,取自iThome網頁:https://www.ithome.com.tw/people/125256\n王思椉(2018年11月12日)。〈【2018數位金融大調查】外匯成年輕世代投資新寵〉,《遠見雜誌》,取自:https://www.gvm.com.tw/article/54791\n安永聯合會計師事務所(2019年6月13日)。《2019 年全球財富管理報告》,取自安永網頁:https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/wealth-and-asset-management/wealth-asset-management-pdfs/ey-global-wealth-management-research-report-2019.pdf\n李沃牆(2019年4月18日)。〈善用AI 提升金融競爭力〉,取自udn聯合新聞網網頁:https://udn.com/news/story/7238/3762231?from=udn-hotnews_ch2\n沈庭安(2017年3月4日)。〈全臺第一個金融聊天機器人!玉山銀搶先用Chatbot提供3大金融業務諮詢〉,取自iThome網頁:https://www.ithome.com.tw/news/112450\n宋宜芳、陳慧菱(2017年2月2日)。〈聊天機器人來了 金融業積極導入 致勝關鍵在大數據〉,取自鉅亨網網頁:https://news.cnyes.com/news/id/3689608\n吳建頤(2019年9月26日)。〈【FinTech進化論】高喊AI-first、Data-only,為什麼可能很危險?〉,《天下雜誌》,取自:https://www.cw.com.tw/article/article.action?id=5097006\n周書暉、林祐全(2011)。〈結合情境與情緒:人機互動理論沿革與發展〉,《傳播與管理研究》,11(1):29-68。\n周令珩(2018)。《以科技接受模型探討金融市場導入機器人理財之可行性》。大同大學資訊經營研究所碩士論文。\n金管會(2019年8月8日)。〈金融業今年預計投入金融科技發展金額之成長率將突破8成〉,取自金管會網頁:https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201908080005&aplistdn=ou=news,ou=multisite,ou=chinese,ou=ap_root,o=fsc,c=tw&dtable=News\n翁秀琪(1992)。《大眾傳播理論與實證》。台北:三民。\n翁秀琪(1993)。〈閱聽人研究的新趨勢_收訊分析的理論與方法〉,《新聞學研究》,47: 1-15。\n徐慧雯(2016)。《聊天機器人使用意願影響因素之研究》。國立臺灣科技大學,資訊管理系碩士論文。\n孫一仕(2019年7月24日)。〈攜手AI擁抱創新路,四大應用讓台灣金融業改頭換面〉,取自智勝文化網頁:https://www.bestwise.com.tw/cross/post.aspx?ipost=3781\n畢恆達(2010)。《教授為什麼沒告訴我:2010全見版》。台北:小畢空間\n陳彥妤(2018)。《探討聊天機器人的信任移轉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。\n陳凱迪(2018)。〈人工智慧發展對金融業之衝擊與因應〉,《財金資訊季刊》,93: 14-22。\n陳君毅(2018年9月17日)。〈Chatbot崛起的時機、失利的現實,以及轉型的夢想〉,取自數位時代網頁:https://www.bnext.com.tw/article/50623/chatbot-the-topic\n陳慧菱(2018年12月4日)。〈國泰金斥資上千萬元推出智能客服 人壽銀行皆成立專責Chatbot訓練師〉,取自鉅亨網網頁:https://news.cnyes.com/news/id/4249938\n陳宛茜(2019年5月19日)。〈林百里和葉丙成談AI世代 預言文科生將逆襲〉,取自聯合新聞網網頁:https://udn.com/news/story/6885/3821444\n張玉佩(2013)。《當代閱聽人研究之理論重構:試論閱聽人的思辨能力》。國立政治大學,新聞研究所博士論文。\n張玉佩、黃如鎂(2016)。〈客家電影《一八九五》的青少年閱聽人 解讀與詮釋〉,《全球客家研究》,7: 135-182。\n張弘一(2017)。《理財機器人的崛起對於財富管理之銀行理財專員的影響》。淡江大學企業管理學系碩士在職專班碩士論文。\n游美惠(2000)。〈內容分析、文本分析與論述分析在社會研究的運用〉,《調查研究-方法與應用》,8: 5-42。\n黃朝秋、賴薇如譯(2018)。《設計聊天機器人:建立對話式體驗》。台北:碁峯資訊。(原書 Amir Shevat. [2017]. Designing Bots: Creating Conversational Experiences. O`Reilly Media,Inc.)\n黃慈恩(2019)。《具個性提示之聊天機器人對電子商務使用者感受與行為之影響》。國立台中科技大學多媒體設計系碩士班碩士論文。\n程士華(2019年6月13日)。〈金融科技使用率增 壯年族群最愛用〉,取自udn聯合新聞網網頁:https://udn.com/news/story/7239/3869142\n彭文志、黃思皓(2019)。〈人工智慧在金融科技上的應用〉,《科學發展》,55: 20-27。\n胡幼慧(1996)。《質性研究 理論、方法及本土女性研究實例》,頁141-158。台北:巨流資訊。\n葉謹睿(2010)。《互動設計概論》。台北:藝術家。\n盧嵐蘭(2007)。《閱聽人與日常生活》。台北:五南。\n遠見雜誌(2017年8月30日)。〈聊天機器人搏感情 服務完成率高達90%〉,取自遠見雜誌網頁:https://www.gvm.com.tw/article/39830\n遠見雜誌(2019年10月1日)。〈2019第二屆《遠見雜誌》數位金融服務最佳銀行大賞〉,取自遠見雜誌網頁:https://gvsrc.cwgv.com.tw/articles/index/14823\n蔡琰、臧國仁(2017)。〈數位時代的「敘事傳播」: 兼論新科技對傳播學術思潮的可能影響〉,《新聞學研究》,131:1-48。\n蕭瑞麟(2011)。《不用數字的研究》。台北:五南。\n蕭瑞麟(2019年10月26日)。〈質性研究鑑定三原則【蕭瑞麟】〉,取自不用數字的研究網頁:https://reswithoutnumbers.blogspot.com/2019/10/blog-post_26.html\n蕭閔云(2019年9月3日)。〈Chabot服務再進化!不只搞定客服,更在互動時勾住消費者的心〉,取自數位時代網頁:https://www.bnext.com.tw/article/54596/chatbot-martech\n蕭俊傑(2019年9月27日)。〈人工智慧與金融應用〉,取自IBM網頁:https://www.ibm.com/blogs/think/tw-zh/2019/09/27/aifinance/\n蘇宇庭(2016年6月6日)。〈聊天機器人掀風潮,對話式電子商務時代起〉,取自數位時代網頁:https://www.bnext.com.tw/article/39832/BN-2016-06-06-184912-218\n二、英文文獻\nAbercrombie, N., & Longhurst, B. (1998). Audiences: A sociological theory of performance and imagination. London: Sage\nACM SIGCHI (1992). Curriculum for human-computer interaction, ACM Special Interest Group on human-computer interaction curriculum development group, New York.\nAnderson, J. A. (1996). The pragmatics of audience in research and theory. In J. A. Hay et al.(Eds), The audience and its landscape. 75-96. Boulder, CO: Westview.\nAlasuutari, P. (Ed.). (1999). Rethinking the media audience. London, UK: Sage.\nBaecker, R. M., Buxton, W. A. S. (1987). Reading in Human-Computer Interaction: A Multi-disciplinary Approach. Los Altos, CA: Morgan Kaufmann\nBannon, L. (1991). From human factors to human actors: The role of psychology and human-computer interaction studies in system design. In J. & Kyng,M. (Eds.), Design at work: Cooperative design of computer systems (pp. 25-44). Hillsdale: Lawrence Erlbaum Associate.\nCard, S, Moran, T, & Newell, A (1983). The psychology of human-computer interaction. Hillsdale, NJ: Erlbaum\nChaozhuo Li, Yu Wu, Wei Wu, Chen Xing, Zhoujun Li, Ming Zhou(2016). Detecting context dependent messages in a conversational environment. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 1990–1999, Osaka, Japan, December 11-17 2016.\nConiam, D. (2014) The Linguistic Accuracy of Chatbots: Usability From an ESL Perspective. Text Talk. 34(5),545–567.\nCorner, J.(1991)Meaning genre and context:the problematics of public knowledge in the new audience studies. In J. Curran and M. Gurevitch (eds).Mass Media and Society, 267-284. London:Edward Arnold.\nDani¨elle Duijst. (2017). Can we improve the user experience of chatbots with personalisation? University of Amsterdam Science Park. (DOI: 10.13140 /RG.2.2.36112.92165)\nDavis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318−339.\nEgger Florian, N. (2000). Towards a model of trust for e-commerce system design. Proc. Of the CHI2000 Workshop: Designing Interactive Systems. from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.33.8610&rep=rep1&type=pdf\nEmerj. (2018). Use cases of AI for customer service – What’s working now, Retrieved July 12 2019, from https://emerj.com/ai-sectoroverviews/ai-for-customer-service-use-cases/\nErickoon, F., & Shultz, J. (1981). When is context? Some issues and methods in the analysis of social competence. In J. L. Green & C. Wallat (Eds.), Ethnography and language in educational settings. 147-160. Norwood, NJ: Ablex Publihing Corporation.\nFetterman, D.M. (2009). Ethnography:step by step (3rd ed.)Thousand Oaks,CA:Sage.\nFiske, J. (1989). Moments of television: Neither the text nor the audience. In E. Seiter, H. Borchers, G. Kreutzner & E. M. Warth (Eds.), Remote Control: Television, Audiences, and Cultural Power (pp. 30-49). New York & London: Routledge.\nFolmer, eelke & Bosch, Jan. (2004). Architecting for usability: a survey. Journal of Systems and Software. 70. 61-78.\nGokue Cho and Jae Young Yun. (2019). UX evaluation of financial service chatbot interactions. Journal of the HCI Society of Korea, 14(2),61-69. Retrieved from https://www.koreascience.or.kr/search.page?keywords=UX+evaluation+of+financial+service+chatbot+interactions.\nGraesser, A. C., Millis, K. K., & Zwaan, R. A. (1997). Discourse comprehension. Annual Review of Psychology, 48, 163-189.\nHall, S. (1973) Encoding and decoding, in S. Hall, D. Hobson, A. Lowe& P. Wills(eds.) Culture, Media, Language (pp.128-138). London: Hutchinson\nHall, S. (1980) Encoding /decoding. In. S. Hall et al. (Eds.), Culture, media, language (pp.128-139). London: Hutchinson.\nHill, J., Ford, W.R., and Farreras, I.G (2015) Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations. Computers in Human Behavior 49, 245–250.\nHibbard, K. M. & Wagner, E. A.(2003)Assessing & Teaching-Reading Comprehension & Pre-Writing. NY: Eye On Education,Inc, 37.\nHoijer, B.(1992) Socio-cognitive structures and television reception. In Media, Culture and Society.l (14),583-603.\nHoffman,D.L. & Novak,T.P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing. 60 (3),50-68.\nHudson, J.& Shapiro, L. (1991). From knowing to telling: the development of children’s scripts, stories, and personal narratives. In A. McCabe & C. Peterson (Eds.), Developing narrative structure (pp. 89-136). Hillsdale, NJ: Lawrence Erlbaum Associates.\nJensen, K.B. & K.E. Rosengren (1990). Five traditions in search of the audience. European Journal of Communication, 5, 207-238.\nJensen, K.B. (1991). Media audience receptions analysis: mass communication as the social production of meaning. In K.B. Jensen and N.W.Jankowski (eds.) (1991) A Handbook of Qualitative Research, (pp. 135-148). London and New York: Routledge.\nLandauer, T. (1990). Relations between cognitive psychology and computer system design. In interfacing thought. J. M. Carroll (ed), Cambridge, MA: MIT Press.\nLegris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191−204.\nLee, Min Kyu & Park, Heejun (2019) Exploring factors influencing usage intention of chatbot – chatbot in financial service. J Korean Soc Qual Manag. 47(4), 755-765.\nLivingstone, S. M. (1990). Making sense of television: The psychology of audience interpretation. Oxford: Pergamon\nMalhotra, Y., Galletta, D.F., Kirsch, L.J. (2008). How endogenous motivations influence user intentions: Beyond the dichotomy of extrinsic and intrinsic user motivations. J. Manag. Inform. Syst. 25(1), 267–300\nMcTear, M., Callejas, Z., & Griol, D. (2016). The conversational interface. Springer.\nMiller W.L. & Crabtree B.F. (1992) Primary Care Research: A Multimethod Typology and Qualitative Road Map. In: W.L. Crabtree & B.F. Miller (Eds.), Doing Qualitative Research. 3-28. Newbury Park CA: Sage.\nMoonkyoung Jang, Yoonhyuk Jung & Seongcheol Kim (2019). Investigating Managers’ Understanding of Chatbot Services for Korean Financial Industry.\nMorley, D. (1980) The Nationwide Audience:Structure and Decoding. British Film Institute Television Monographs,11,London:BFI.\nNorman, D., Ortony, A., & Russell, D. (2003). Affect and machine design: Lessons for the development of autonomous machines. IBM Systems Journal. 42(1),38-44.\nO’Brien, G. (2017). The user experience of creating a chatbot. Retrieved June 26, 2017, from https://tutorials.botsfloor.com/the-userexperience-of-creating-a-chatbot-1f9055496349\nOskar Hansson. (2018). Exploring users’ perception of chatbots in a bank environment. MALMO University.\nPetter Bae Brandtzæg and Asbjørn Følstad (2017). Why people use chatbots. International Conference on Internet Science.\nPetter Bae Brandtzæg and Asbjørn Følstad (2017). Chatbots and the new world of HCI. Interactions 24(4), 38-42. Retrieved June 23, 2017, from: https://www.researchgate.net/publication/317920872_Chatbots_and_the_new_world_of_HCI\nPetter Bae Brandtzæg and Asbjørn Følstad (2018). Chatbots: changing user needs and motivations, Interactions 25(5), 38-43. Retrieved August 22, 2018, from: https://www.researchgate.net/publication/327191388_Chatbots_changing_user_needs_and_motivations\nQuarteroni,S.,& Manandhar, S. (2009).Designing an interactive open-domain question answering system. Natural Language Engineering. 15(1),73-95.\nRogers, E. M. (2002). Diffusion of preventive innovations. Addictive Behaviors, 27(6), 989−993.\nRouse, M (2018).What is chatbot .TechTarget .Retrieved Jane 05 2018, from: http://searchcrm.techtarget.com/definition/chatbot\nJensen, S.S. & Limperos, A.M.(2013). Uses and grats 2.0: new gratifications for new media. J. Broadcast. Electron. 57(4), 504–525\nSommer, R. (2012). The merger of classical and postclassical narratologies and the consolidated future of narrative theory. Interdisciplinary E-Journal for Narrative Research. Retrieved November 11, 2015, from http://www.diegesis.uni-wuppertal.de/index.php/diegesis/article/view/96/93\nSundar, S.S., Limperos, A.M. (2013). Uses and grats 2.0: new gratifications for new media. J. Broadcast. Electron, 57(4), 504–525\nSuchman, L. A. (1987). Plans and situated actions: the problem of humanmachine communication. Cambridge university press.\nSwaby B.E.R.(1989).Diagnosis and correction of reading difficulties. Boston: Allyn and Bacon.\nTakuma Okuda & Sanae Shoda. (2018). AI-based chatbot service for industry. Fujitsu Scientific and Technical Journal.,54 (2), 4-8.\nTatai, G., Csorda´s, A., Kiss, ´A., Szalo´, A., & Laufer, L. (2003). Happy chatbot, happy user. In International workshop on intelligent virtual agents, 5–12.\nTuva Lunde Smestad (2018). Personality matters! Improving the user experience of chatbot interfaces. Norwegian University of Science and Technology Department of Design.\nvan Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. New York: Academic Press.\nWeizenbaum, J. (1966). ELIZA- a computer program for the study of natural language communication between man and machine. Communication of the ACM 9 (1), 36–45.
描述: 碩士
國立政治大學
傳播學院碩士在職專班
106941005
資料來源: http://thesis.lib.nccu.edu.tw/record/#G0106941005
資料類型: thesis
Appears in Collections:學位論文

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