研究生: |
林書宇 Lin, Shu-Yu |
---|---|
論文名稱: |
線上音樂之探索式尋求行為研究 A Study on Exploratory Online Music Information-Seeking Behavior |
指導教授: |
卜小蝶
Pu, Hsiao-Tieh |
學位類別: |
碩士 Master |
系所名稱: |
圖書資訊學研究所 Graduate Institute of Library and Information Studies |
論文出版年: | 2017 |
畢業學年度: | 105 |
語文別: | 中文 |
論文頁數: | 119 |
中文關鍵詞: | 探索式資訊尋求行為 、音樂資訊檢索行為 、線上音樂 、新音樂尋求 |
英文關鍵詞: | Exploratory information seeking behavior, Music information retrieval, Online music, Exploratory music seeking |
DOI URL: | https://doi.org/10.6345/NTNU202202236 |
論文種類: | 學術論文 |
相關次數: | 點閱:166 下載:27 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
聆聽音樂為一般大眾常見且重要的休閒活動之一,隨著網路及數位化科技蓬勃發展,線上數位音樂的數量及服務平台成長快速,人們逐漸從聆聽實體音樂轉移至線上數位音樂。同時,人們對音樂的興趣常有變化,尋找未曾聆聽過的新音樂有相當大的需求。此外,音樂搜尋不同於一般文字檢索,由於音樂缺乏足夠的文字資訊,使用者不易以類似關鍵字的方式來表達需求,特別是一無所知的新音樂,更是難以掌握。本研究主要目的為瞭解在線上數位音樂環境中,一般青壯年使用者探索新音樂的動機、需求、及尋求歷程。
本研究以18至45歲的青壯年使用者為對象,採用問卷、日誌、訪談、實驗等多元方法。問卷主要收集使用者日常聆聽音樂喜好與線上數位音樂平台之使用經驗等;日誌用來瞭解使用者在日常生活中,對新音樂探索的動機、需求及尋找歷程;實驗是用以觀察不同使用者在相同探索情境中的尋求行為異同;訪談則是深入瞭解使用者主觀想法,並驗証前述所收集資料一致性。本研究共收集951份有效問卷,並從問卷填答者中邀請15位參與後續之日誌、實驗及訪談。
研究結果發現,就聆聽音樂及使用經驗,使用者多獨自聆聽音樂;聆聽場所以家中及行動中為主;聆聽時段以夜間為主;聆聽的載具愈來愈偏重智慧型手機;YouTube是最主要聆聽與新音樂探索平台,其次為Spotify、KKBOX等線上音樂平台;主要聆聽音樂類型包括流行樂、搖滾樂、獨立音樂等。而就使用者的新音樂探索動機,其影響因素可區分為個人及社會性二類因素,本研究進一步依觸發情境再細分為九種動機類型,個人因素包括個人興趣、滿足好奇、回憶觸發、喜新厭舊、放鬆心情、學習新知、排解無聊;社會性因素包括迎合潮流、自我表現。就使用者的新音樂資訊需求及尋求歷程,其主要資訊來源為被動偶遇,但仍有超過一半的使用者會主動探索新音樂;而在主動探索中又以關鍵字搜尋及瀏覽為主要接收資訊管道;所使用的探索平台以YouTube為主,Spotify、KKBOX等線上音樂平台也是重要探索管道;所使用的搜尋策略除關鍵字搜尋外,也會大量瀏覽平台或系統所提供之分類及推薦資訊,例如熱門音樂排行榜、音樂類型目錄等;而在搜尋與瀏覽的過程中,使用者樂於試探點選感興趣的新音樂,並不排斥與原有音樂偏好無關之音樂等。新音樂的探索歷程,並不一定為線性進行,且探索過程與探索結果的界線模糊,在整個新音樂探索的歷程中,各項行為特性彼此連結、相互影響;本研究最後依據前述結果,整理出新音樂探索式尋求之概念模式,並針對使用者及線上音樂平台提出改善新音樂探索效益之建議。
Music listening is an important leisure activity for general public. With the rapid growth of online music and related services, more and more people tend to listen to online music rather than music from traditional channels. Meanwhile, people’s music interests are dynamic changing and the need for new music is commonly found in music seeking. Unlike searching textual information, people often find it difficult to express their needs by keywords, particularly they have no clues in new or unknown music finding. Such seeking process was termed as music exploring in this study, and the researcher attempts to collect new music finding data from the subjects of 18-45, and analyze their motivation, needs and searching process.
This study used multiple research methods. Questionnaire method for collecting data about users' online music listening habits and using experiences. Diary method to record users' motivation, needs and seeking process about new music exploration in daily life. Experiment method use the same scenario to compare differences between every participants' seeking behavior. And interview for getting more implicit information from users. In the end of data collecting stage, we received 951 questionnaire answers and had 15 research participants.
Results show that most of the users prefer to listen to music while they're staying at home or moving, and tend to listen to music alone in the night. According to the data, we can clearly find out that devices which users used more to listen online music are smart phones. YouTube is the most popular service followed by online music services such as Spotify, KKBOX etc., and top genres are pop, rock, indie music. In addition to that, there are 2 types of new music exploratory motivation, Individual factor & Social factor. The main source of new music information is encounter, but still, over 50% of users would explore music initiatively. Services user used to explore music also as same as what they listen to. In the music exploratory process, except for the keyword search, users would greatly browse information (Top ranking charts, genre catalogs etc.) served from online music services, and would be more willing to try the music they might interest in, even the music differ from what they love.
Exploratory music seeking process could be a linea process or not. In the process, every behavior all connect and effect to each other, and boundaries between steps are fuzzy. In the end of this study, we present a model of exploratory music seeking process and suggestions to users and online music services for improving their services about music exploration.
中文文獻:
T客邦(2015年8月17日)。串流平台該怎麼選?Spotify / Google / LINE / KKBOX
4大平台分析。檢自:http://www.techbang.com/posts/25238-streaming-music-
platform-that-you-choose-4-platform-than-for-you-to-watch
中華民國交通部公路總局(2015)。公路汽車客運駕駛員性別統計分析。檢自:
https://goo.gl/HeHZ6s
李忠諭(2009)。線上音樂之發展歷程與產業現況。網路社會學通訊期刊,78。
李俐雯(2012)。線上音樂下載之決策行為調查研究(未出版之碩士論文)。國立
臺灣師範大學圖書資訊學研究所,臺北市。
邱銘心(2012)。資訊發現。圖書館學與資訊科學大辭典。檢自:
http://terms.naer.edu.tw/detail/1679180/
林怡君(2010)。網路影音分享網站之使用者檢索行為研究(未出版之碩士論文)。
國立臺灣師範大學,臺北市。
洪元元(2009)。從使用者音樂聆賞歷程探討線上音樂分類架構(未出版之碩士
論文)。國立臺灣大學,臺北市。
唐牧群(2007)。淺談探索式搜尋:ACM會後心得。中華圖書資訊學教育學會會
訊,28,19-21。
唐牧群、謝伊柔(2016)。社會導覽工具評估之研究:以亞馬遜網路書店為例。
圖書資訊學研究,10(2),181-228。
國立臺灣藝術教育館(2005)。何謂數位音樂。檢自:
http://web.arte.gov.tw/digital_teacher/art/music/page02.htm
張映涵(2012)。網路影音休閒之遊歷行為研究(未出版之碩士論文)。國立臺灣
師範大學圖書資訊學研究所,臺北市。
創市際市場研究顧問公司(2015)。線上音樂服務調查與音樂相關類型網站使用
概況。創市際雙週刊,54,1-23。
創市際市場研究顧問公司(2016)。2015年台灣網路使用概況回顧。創世紀雙週
刊,58,1-31。
創市際市場研究顧問公司(2016)。社群服務調查與使用概況。創世紀雙週刊,
67,1-24
曾毓忠(2005)。何謂數位音樂。國立臺灣藝術教育館。檢自:
http://web.arte.gov.tw/digital_teacher/art/music/page02.htm
單維彰(2012)。數位音訊,選修數學(甲版)上冊,12-13。檢自:
http://www.grandeast.com.tw/DocUploads/Math/%E9%81%B8%E4%BF%AE%E6%95%B8%E5%AD%B8(%E7%94%B2%E7%89%88)%E4%B8%8A%E5%86%8A%20%E8%AA%B2%E5%A4%96%E8%AE%80%E7%89%A9.pdf
葉俊廷(2010)。工作與休閒時段與遊戲時間之研究:以網頁型線上遊戲為例(未
出版之碩士論文)。國立交通大學資訊學院資訊學程,新竹市。
遠雄人壽(2015)。臺灣地區傷害保險個人職業分類表。檢自:
https://www.fglife.com.tw/ow/Ftp.action?UUID=80c04e9d2efd49e4b00e2681af
d037b8
廖家慧(2011)。使用者音樂描述及音樂資訊需求描述之分析研究(未出版之碩
士論文)。國立臺灣師範大學圖書資訊學研究所,臺北市。
維基百科(2016)。串流媒體。檢自:
https://zh.wikipedia.org/w/index.php?title=%E6%B5%81%E5%AA%92%E4%BD%93&oldid=41956187
趙廣絜(2015)。當音樂產業走入數位時代。喀報,226。檢自:
https://ir.nctu.edu.tw/bitstream/11536/125443/1/8785.pdf
賴玲玲(2012)。資訊尋求行為。圖書館學與資訊科學大辭典。檢自:
http://terms.naer.edu.tw/detail/1679134/
英文文獻:
Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary Methods: Capturing Life as It is
Lived. Annual review of psychology, 54(1), 579-616.
Castañón, G. D., Caron, A. L., Saligrama, V., & Jodoin, P. M. (2012). Exploratory
Search of Long Surveillance Videos. Proc. 20th ACM International Conference on
Multimedia. pp. 309-318
Chamberlain, A., & Crabtree, A. (2016). Searching for Music: Understanding the
Discovery, Acquisition, Processing and Organization of Music in a Domestic
Setting for Design. Personal and Ubiquitous Computing, 20(4), 559–571.
Chamorro‐Premuzic, T., & Furnham, A. (2007). Personality and Music: Can Traits
Explain How People Use Music in Everyday Life?. British Journal of Psychology,
98(2), 175-185.
Cunningham, S. J., Bainbridge, D., & McKay, D. (2007). Finding New Music: A Diary
Study of Everyday Encounter With Novel Songs. Proc. 8th ISMIR. pp. 83-88.
Dalton, M. K., Ferraro, E. J., Galuardi, M., Robinson, M. L., Stauffer, A. M., & Walls,
M. T. (2016). On the Incorporation of Psychologically-Driven'Music'Preference
Models for Music Recommendation (Doctoral dissertation).
Downie, J. S. (2008). The Music Information Retrieval Evaluation Exchange (2005–
2007): A Window Into Music Information Retrieval Research. Acoustical Science
and Technology, 29(4), 247-255.
Ericsson. (2017). Ericsson Mobility Report. Retrieved from:
https://www.ericsson.com/assets/local/mobility-report/documents/2017/ericsson-
mobility-report-june-2017.pdf
Exact Target. (2014). Mobile Behavior Report. Retrieved from:
https://www.marketingcloud.com/sites/exacttarget/files/deliverables/etmc-2014mobilebehaviorreport.pdf
Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter Bubbles, Echo Chambers, and Online
News Consumption. Public Opinion Quarterly, 80(S1), 298-320.
Golovchinsky, G., Adcock, J., Pickens, J., Qvarfordt, P., & Back, M. (2008). Cerchiamo:
a Collaborative Exploratory Search Tool. Proc. Computer Supported Cooperative
Work, 8-12.
Glowacka, D., Ruotsalo, T., Konuyshkova, K., Kaski, S., & Jacucci, G. (2013).
Directing Exploratory Search: Reinforcement Learning from User Interactions
With Keywords. Proc. 18th International Conference on Intelligent User Interfaces. pp. 117-128.
Herrera, P., Resa, Z., & Sordo, M. (2010). Rocking Around the Clock Eight Days a Week:
an Exploration of Temporal Patterns of Music Listening. Proc. 1st Workshop On
Music Recommendation And Discovery.
Inskip, C., Macfarlane, A., & Rafferty, P. (2012). Towards the Disintermediation of
Creative Music Search: Analysing Queries to Determine Important Facets.
International Journal on Digital Libraries, 12(2-3), 137-147.
International Federation of the Phonographic Industry. (2016). Global Music Report
2016. Retrieved from: http://www.ifpi.org/downloads/GMR2016.pdf
Janiszewski, C. (1998). The Influence of Display Characteristics on Visual Exploratory
Search Behavior. Journal of Consumer Research, 25(3), 290-301.
Kim, S. M. (2015). Towards Organizing and Retrieval Classical Music Based on
Functional Requirements for Bibliographic Records (FRBR) (Doctoral
Dissertation).
Krause, A. E., North, A. C., & Hewitt, L. Y. (2015). Music-Listening in Everyday Life:
Devices and Choice. Psychology of music, 43(2), 155-170.
Krestel, R., Demartini, G., & Herder, E. (2011). Visual Interfaces for Stimulating
Exploratory Search. Proc. 11th Annual International ACM/IEEE Joint Conference
on Digital Libraries. pp. 393-394.
Kuhlthau, C. C. (2004). Seeking meaning: A process approach to library and
information services. Libraries Unltd Incorporated.
Laplante, A. (2014). Improving Music Recommender Systems: What Can We Learn
From Research on Music Tastes. Proc. 15th ISMIR. pp. 451-456.
Lee, J. H., & Cunningham, S. J. (2012). The Impact (or Non-impact) of User Studies in
Music Information Retrieval. Proc. 13th ISMIR. pp.391-396.
Lee, J. H., & Cunningham, S. J. (2013). Toward an Understanding of the History and
Impact of User Studies in Music Information Retrieval. Journal of Intelligent
Information Systems, 41(3), 499-521
Lee, J. H., Kim, Y. S., & Hubbles, C. (2016). A Look at the Cloud from Both Sides Now:
An Analysis of Cloud Music Service Usage. Proc. 17th ISMIR. pp. 299-305.
Marchionini, G. (2006). Exploratory Search: From Finding to Understanding.
Communications of the ACM, 49(4), 41-46.
Marchionini, G. (2006). Human Performance Measures for Video Retrieval. Proc. 8th
ACM International Workshop on Multimedia Information Retrieval. pp. 307-312.
Merriam, A. P. (1964). The Anthropology of Music. Northwestern University Press.
Nielsen. (2016). Music360 2016 - Highlights. Retrieved from:
http://www.nielsen.com/us/en/insights/reports/2016/music-360-2016-highlights.html
Nielsen. (2016). 2016 U.S. Music Mid-Year Report. Retrieved from:
http://www.nielsen.com/us/en/insights/reports/2016/2016-us-music-mid-year-report.html
O’Brien, H. L., & Toms, E. G. (2013). Examining the Generalizability of the User
Engagement Scale (UES) in Exploratory Search. Information Processing &
Management, 49(5), 1092-1107.
Pachet, F., Roy, P., & Cazaly, D. (2000). A Combinatorial Approach to Content-Based
Music Selection. IEEE MultiMedia, 7(1), 44-51.
Pichl, M., Zangerle, E., & Specht, G. (2014). Combining Spotify and Twitter Data for
Generating a Recent and Public Dataset for Music Recommendation. In
Grundlagen von Datenbanken. pp. 35-40.
Pickens, J., Golovchinsky, G., Shah, C., Qvarfordt, P., & Back, M. (2008). Algorithmic
Mediation for Collaborative Exploratory Search. Proc. 31st Annual International
ACM SIGIR Conference on Research and Development in Information Retrieval.
pp. 315-322.
Rentfrow, P. J., & Gosling, S. D. (2003). The Do Re Mi's of Everyday Life: The
Structure and Personality Correlates of Music Preferences. Journal of Personality
and Social Psychology, 84(6), 1236-1256.
Salimpoor, V. N., van den Bosch, I., Kovacevic, N., McIntosh, A. R., Dagher, A., &
Zatorre, R. J. (2013). Interactions Between the Nucleus Accumbens and Auditory
Cortices Predict Music Reward Value. Science, 340(6129), 216-219.
Skov, M., & Ingwersen, P. (2014). Museum Web Search Behavior of Special Interest
Visitors. Library & Information Science Research, 36(2), 91-98.
Smith, E. (2012, August 14). Forget CDs. Teens are Tuning in to YouTube. Nielsen
Survey Says More Youngsters Listen to Music via Video-Sharing Site, While
Some Adults Still Groove to Cassettes. The Wall Street Journal, p. B3.
Tait, J. I. (2006). Exploratory Search: Image Retrieval Without Deep Semantics, Proc.
IFIP International Conference on Artificial Intelligence Applications and
Innovations. pp. 566-574.
Tan, W. K., & Tan, Y. J. (2012). An Exploratory Investigation of the Investment
Information Search Behavior of Individual Domestic Investors. Telematics and
Informatics, 29(2), 187-203.
Tarrant, M., North, A. C., & Hargreaves, D. J. (2000). English and American
Adolescents' Reasons for Listening to Music. Psychology of Music, 28(2), 166-
173.
White, R. W., Kules, B., & Drucker, S. M. (2006). Supporting Exploratory Search,
Introduction, Special Issue, Communications of the ACM. Communications of the
ACM, 49(4), 36-39.
Wilson, M. L., & Elsweiler, D. (2010). Casual-Leisure Searching: the Exploratory
Search Scenarios that Break Our Current Models. Proc. 4th Workshop on Human-
Computer Interaction and Information Retrieval. pp. 28-31.
Wilson, T.D. (1999). Model in Information Behavior Research. Journal of
Documentation, 55(3), 249-257.
Wunsch-Vincent, S., & Vickery, G. (2004). Digital Broadband Content: Music. Proc.
Working Party on the Information Economy.