網路影音分享平台如YouTube是近年來相當熱門的網路資訊服務之一。隨著網路影音內容愈加多元豐富，其不僅成為使用者重要的休閒娛樂來源，同時也是上網搜尋的重要資源之一。就使用者網路搜尋行為的相關研究中，過去多偏重認知層面的瞭解，近來已有一些研究注意到情感面向在使用者搜尋過程中的重要性。本研究以網路影音分享平台為研究場域，結合正向心理學中之沉浸理論，嘗試分析探討使用者在影音檢索過程中，所產生之沉浸特徵，並進一步瞭解影音檢索行為與沉浸過程之關聯。

本研究主要採用檢索記錄分析法。研究對象為7名長期且經常使用網路影音分享平台之20-39歲、且具影音檢索沉浸經驗者。研究內容主要為蒐集受訪者日常生活之影音檢索行為，為期二個月檢索記錄的蒐集，共計取得167筆檢索記錄，經受訪者自評其中70筆為沉浸經驗之記錄，有效記錄為25筆。除上述所得之影音檢索記錄外，研究者也同時進行個別訪談及邀請受訪者填寫問卷。

研究結果發現，不論工作導向或休閒導向之影音檢索任務，受訪者皆有沉浸現象產生。依據訪談與研究者觀察，沉浸現象的產生，除影音檢索任務特性外，也與受訪者個人背景知識與興趣有關，此外，受訪者與媒介互動情形也會有影響。進一步分析，在檢索的過程中，受訪者所觀看的影音內容是促發沉浸的主因，換言之，受訪者對影音內容所知與所感會直接影響其是否產生沉浸現象；此外，在檢索過程中，使用者與媒介的互動，包括使用流暢度、回饋線索等，也會影響使用者的沉浸感受。受訪者主要以關鍵字檢索來搜尋影音，而透過關鍵字的聯想與轉化策略，受訪者常能藉此發現未預期且感到驚喜的影音。而瀏覽系統所提供之各類影音相關資訊（如影音上傳者之註解及使用者評論），也會間接影響受訪者更加投入沉浸的氛圍。

在未來研究，若能提高研究對象之配合意願，並且擴大研究樣本，對於個人背景與特質對沉浸的影響或關係，進行更深入的探討。同時，配合長期觀察，蒐集更完整、真實自然的的影音搜尋與使用記錄，將有助瞭解使用者在使用網路影音分享平台時，透過興系統互動、磨合、學習適應後的行為變化。此外，對於何種影音內容要素會促使受訪者產生沉浸現象，以及部份未產生沉浸現象的影音檢索任務，使用者的行為表現與引發使用者產生何種內心感受，也值得進一步分析。

In recent years, video sharing website, one of the network information services is very popular, such as YouTube. With the increasingly of video content, it is not only become an important source of entertainment, but also an important resource for information. About user behavior studies, some scholars pay attention to cognitive aspects and emotional aspects of the process. They emphasize the importance of cognitive and emotional aspects. This study combines video sharing website and flow theory, tries to analyze user’s video search behavior and flow experience for reference of further studies.

This study used search record analysis. The seven subjects, among 20-39 years old, were long-term and frequent use of online video sharing website, and had flow experience of video search process. It mainly collected the video search behavior record of daily life for two months. Total of 167 records to search records obtained by the subjects, 70 self-assessment records of having flow experience, effectively logged as 25 records. In addition to the search record analysis, the researcher also used interview and questionnaire.

The results showed that, regardless of orientation for leisure or job video search tasks, they had flow experience. According to the interview, flow experience had relations with video search tasks and the subjects on personal background knowledge and interests. In addition, the subjects are also affected by interactions with the media. Further analysis, the search process, the subjects are viewing video content is the main cause of flow, in other words, the subjects are aware of content will have a direct impact on flow. Besides the search process, the subjects interact with the system will also affect the user's flow experience, including the use of fluency, feedback cues and through keyword association and transformation strategy, the subjects can be unexpected to find the video and was pleasantly surprised. Various types of audio and video information such as user comments, will also indirectly affect the subjects were more immersed into the atmosphere.

In the future, to increase the subjects with the intention to co-operate and expand the research samples, for understanding personal background and characteristics of the impact of flow or relationship. Meanwhile, with the long-term observations, collecting more complete and realistic nature of video search behaviors, will help to understand the user in the use of video sharing website, and behavior changes with system interaction. Moreover, what kinds of video content elements will lead to the flow experience, and the user's behavior and what the feelings caused by some search tasks which having no flow experience, is worthy of further analysis.

Chen, H. (2006). Digitization of the experience sampling method: Transformation, implementation, and assessment. Social Science Computer Review, 24(1), 106.
Chen, H. (2006). Flow on the net-detecting Web users' positive affects and their flow states. Computers in Human Behavior, 22(2), 221-233.
Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of Web activities. Computers in Human Behavior, 15(5), 585-608.
Cheng, X., Dale, C., & Liu, J. (2007). Understanding the Characteristics of Internet Short Video Sharing: YouTube as a Case Study. Arxiv preprint arXiv:0707.3670.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety (1st ed.). San Francisco: Jossey-Bass Publishers.
Csikszentmihalyi, M. (1990). Flow : the psychology of optimal experience (1st ed.). New York: Harper & Row.
Csikszentmihalyi, M., & Csikszentmihalyi, I. S. (1988). Optimal Experience:Psychological Studies of Flow in Consciousness. UK: Cambridge University Press.
Csikszentmihalyi, M., & LeFevre, J. (1989). Optimal Experience in Work and Leisure. [doi:]. Journal of Personality and Social Psychology, 56(5), 815-822.
Cunningham, S., & Nichols, D. (2008). Finding video on the web. Retrieved 12.30, 2009, from http://www.cs.waikato.ac.nz/pubs/wp/2008/
Deborah, R. (2007). Social Search Comes of Age. Information Outlook, 11(8), 19.
Douglas, Y., & Hargadon, A. (2000). The pleasure principle: immersion, engagement, flow. Paper presented at the Proceedings of the eleventh ACM on Hypertext and hypermedia.
Ellis, G. D., Voelkl, J. E., & Morris, C. (1994). Measurement and analysis issues with explanation of variance in daily experience using the flow model. Journal of Leisure Research, 26(4), 337.
Evans, B. M., & Chi, E. H. (2009). An elaborated model of social search. Information Processing & Management, In Press, Corrected Proof.
Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., & Smyth, B. (2007). ASSIST: adaptive social support for information space traversal.
Finneran, C. M., & Zhang, P. (2002). The challenges of studying flow within a computer-mediated environment.
Finneran, C. M., & Zhang, P. (2003). A person-artefact-task (PAT) model of flow antecedents in computer-mediated environments. International Journal of Human-Computer Studies, 59(4), 475-496.
Finneran, C. M., & Zhang, P. (2005). Flow in computer-mediated environments: promises and challenges. Communications of the Association for Information Systems, 15, 82-101.
Ghani, J. A. (1995). Flow in Human Computer Interaction: Test of a Model. In J. M. Carey (Ed.), Human factors in information systems: emerging theoretical bases (pp. 291-311). New Jersey: Ablex Publishing Corporation.
Ghani, J. A., & Deshpande, S. P. (1994). Task Characteristics and the Experience of Optimal Flow in Human—Computer Interaction. The Journal of Psychology: Interdisciplinary and Applied, 128(4), 381 - 391.
Halvey, M., & Jose, J. (2009). The role of expertise in aiding video search.
Halvey, M., & Keane, M. (2007). Analysis of online video search and sharing.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50.
Hollink, L., Nguyen, G. P., Koelma, D., Schreiber, A. T., & Worring, M. (2005). Assessing User Behaviour in News Video Retrieval. Paper presented at the IEE proceedings on Vision, Image and Signal Processing.
Jackson, S., & Marsh, H. (1996). Development and validation of a scale to measure optimal experience: The Flow State Scale. Journal of sport and exercise psychology, 18, 17-35.
Kang, X., Zhang, H., Jiang, G., Chen, H., Meng, X., & Yoshihira, K. (2009). Understanding Internet Video sharing site workload: A view from data center design.. Journal of Visual Communication and Image Representation, In Press, Corrected Proof.
Kozinets, R. V. (1998). On Netnography: Initial Reflections on Consumer Research Investigations of Cyberculture. Advances in Consumer Research, 25(1), 366-371.
Kozinets, R. V. (2002). The Field Behind the Screen: Using Netnography for Marketing Research in Online Communities. Journal of Marketing Research (JMR), 39(1), 61-72.
Kuhlthau, C. (1991). Inside the search process: Information seeking from the user's perspective. Journal of the American Society for Information Science, 42(5), 361-371.
Mathwick, C., & Rigdon, E. (2004). Play, Flow, and the Online Search Experience. Journal of Consumer Research, 31(2), 324-332.
Moneta, G. B., & Csikszentmihalyi, M. (1996). The Effect of Perceived Challenges and Skills on the Quality of Subjective Experience. Journal of Personality, 64(2), 275-310.
Nahl, D. (2004). Measuring the affective information environment of web searchers. Proceedings of the American Society for Information Science and Technology, 41(1), 191-197.
Nahl, D. (2005). Affective and cognitive information behavior: Interaction effects in Internet use. Proceedings of the American Society for Information Science and Technology, 42(1), NA.
Nielsen. (2009, 04.22). Online Engagement Deepens Aa Social Media And Video Sites Reshape The Interent. Nielsen Reports. Retrieved from http://blog.nielsen.com/nielsenwire/nielsen-news/online-global-landscape-0409/
Novak, T., & Hoffman, D. (1997). Measuring the flow experience among web users. Interval Research Corporation, 31.
Novak, T., Hoffman, D., & Yung, Y. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22-42.
Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The Influence of Goal-Directed and Experiential Activities on Online Flow Experiences. Journal of Consumer Psychology (Lawrence Erlbaum Associates), 13(1/2), 3.
Ohshima, H., Jatowt, A., Oyama, S., Nakamura, S., & Tanaka, K. (2009). Towards Improving Web Search: A Large-Scale Exploratory Study of Selected Aspects of User Search Behavior.
Pace, S. (2004). A grounded theory of the flow experiences of Web users. International Journal of Human-Computer Studies, 60(3), 327-363.
Parrott., W. G. (2000). Emotions in Social Psychology. Philadelphia: Psychology Press.
Plutchik, R. (1980). Emotion, a psychoevolutionary synthesis. New York: Harper & Row.
Privette, G. (1983). Peak experience, peak performance, and flow: A comparative analysis of positive human experiences. Journal of Personality and Social Psychology, 45(6), 1361-1368.
Richard, M.-O., & Chandra, R. (2005). A model of consumer web navigational behavior: conceptual development and application. Journal of Business Research, 58(8), 1019-1029.
Russell, J. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161-1178.
Russell, J. (1991). Culture and the categorization of emotions. Psychological bulletin, 110(3), 426-450.
Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American Psychologist, 55(1), 5-14.
Shoham, A. (2004). Flow experiences and image making: An online chat-room ethnography. Psychology and Marketing, 21(10), 855-882.
Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interactions. Computers in Human Behavior, 9(4), 411-426.
Xia Skadberg, Y., & Kimmel, J. R. (2004). Visitors' flow experience while browsing a Web site: its measurement, contributing factors and consequences. Computers in Human Behavior, 20(3), 403-422.

翁鵲嵐、鄭玉屏、張志傑譯 (2005)。情感設計：我們為何喜歡(或討厭)日常用品 (原作者Norman, D. A.)。臺北市：田園城市文化。(原著出版年2004)。
池文海、邱天佑、賴慧芬 (2009)。探討瀏覽影音部落格沉浸經驗的前因與後果。姜國輝(主持人)，第十二屆電子商務學術研討會議。臺北縣：臺北大學資訊管理研究所。
林怡君(2010)。網路影音分享網站之使用者檢索行為研究. 國立師範大學圖書資訊學研究所，未出版，臺北。
徐純慧、施素明 (2005)。體驗型及目標導向型活動影響網際網路沉浸之探討。電子商務研究，3(2)，193-209。
創市際市場研究顧問公司(2009) 。2009年11月創市際線上影音小調查。取自http://www.insightxplorer.com/specialtopic/2009_11_video.htm
創市際市場研究顧問股份有限公司 (2009a)。2009年5月創市際線上影音篇。 取自http://www.insightxplorer.com/specialtopic/2009_5_video.htm
創市際市場研究顧問股份有限公司(2009b)。線上影音正夯！三成網友一星期至少使用一次影音分享平台。取自http://www.insightxplorer.com/news/news_05_26_09.html
楊佩樺、林怡君、卜小蝶(2009)。網路影音分享平台之使用行為初探。林信成(主持人) ，2009圖書館與資訊社會研討會。台北縣：輔仁大學圖書資訊學系。
楊純青、陳祥 (2006) 。 網路心流經驗研究中之挑戰: 從效度觀點進行檢視與回顧。資訊社會研究，11，145-176。
蘇慧堅、鍾燕宜 (2004)。閱讀心流經驗於出版行銷策略之研究。出版與管理研究，1(1)，79-132。