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유튜브 오디오북 콘텐츠의 활용 방식과 이용자 반응에 관한 연구

An Analysis of YouTube Audiobook Content Creation and User Responses

  • 정다희 (동덕여자대학교 문헌정보학전공)
  • 투고 : 2025.05.25
  • 심사 : 2025.06.09
  • 발행 : 2025.06.30

초록

본 연구는 유튜브 오디오북 콘텐츠를 중심으로 디지털 독서 환경에서의 저작권 표기 실태와 오디오북에 대한 이용자 반응을 분석하여 무료 오디오북 이용 현황과 문제점을 탐색하였다. 조회수가 가장 높은 100건의 메타데이터와 댓글을 분석한 결과, 오디오북의 45%가 원작 도서나 출판사에 대한 저작권을 표기하지 않고 광고 링크를 게시하고 있어 유튜브 오디오북의 저작권 관리가 필요한 것을 확인할 수 있었다. 댓글 8,192건에 대한 빈도 분석, 키워드 네트워크 분석, 이용자 반응 분석 결과 단어 '듣다', '감사하다', '좋다'와 같은 단어가 자주 등장하였다. 이는 오디오북에 대한 설명이나 긍정적 감정의 반응이 주를 이루어 오디오북이 단순한 정보 전달 매체를 넘어 이용자에게 정서적 치유를 제공하고 다른 사람과 감성적 상호작용을 하는 기능을 하고 있음을 시사한다. 연구 결과를 바탕으로 창작자를 보호할 수 있는 오디오북 저작권 관리의 필요성을 제시하고 정서적 치유를 위한 오디오북 독서프로그램 서비스의 기획을 제안하였다.

This study explores the current state and challenges of YouTube audiobook usage by analyzing copyright labeling and user responses to YouTube audiobook contents within the context of digital reading environments. An analysis of metadata and user comments from the 100 most-viewed audiobook videos showed that 45% of the contents did not include proper copyright attribution. Using frequency analysis, keyword network analysis, and user response analysis, analysis on 8,192 user comments showed that words 'listening', 'thank you', and 'good' were mostly used. Based on the results, this study proposes the necessity of audiobook copyright management, along with the development of public library audiobook programs for emotional support and wellness.

키워드

참고문헌

  1. Ahn, Hyun Woo (2023). A study on the satisfaction and reuse intention of E-books? Audio-books? Chat-books: focusing on the expectancy disconfirmation theory. Studies of Korean Science, 49(2), 53-82.
  2. Ahn, Hyun Woo, Kim, Sung Ju, & Park, Seong Eun (2021). A study on audiobook recognition and success factors: focusing on multitasking factors and media-specific comparison. Studies of Korean Science, 47(2), 5-29. https://doi.org/10.21732/skps.2021.99.5
  3. Hyun, Young-sup (2022). Trends of YouTube contents and impact factors on contents' hits related with human resource development. The Korean Journal of Human Resource Development Quarterly, 24(3), 319-354.
  4. Jang, Yei-Beech (2022). A study on audiobook users' audiobook use motivations, usage patterns, and audiobook reading behavior. The Journal of the Korea Contents Association, 22(11), 254-265. http://doi.org/10.5392/JKCA.2022.22.11.254
  5. Jo, Gi Jun, Nam, Kwang Min, Wu, Mingliu, & Choi Hanbyul (2024). Listening to books: a study on the value system of audiobook users. The Journal of Internet Electronic Commerce Research, 24(4), 81-97. https://doi.org/10.37272/JIECR.2024.08.24.4.81
  6. Kim, Hyoung-Jee & Kim, Junghwan (2021). Why do we listen to books? exploring factors affecting the purchase intention of audiobooks. The Journal of the Korea Contents Association, 21(5), 118-128. https://doi.org/10.5392/jkca.2021.21.05.118
  7. Kim, Hyoung Ju, Moon, Jong Min, & Kim, Pan Koo (2021). An analysis study on the quality of article to improve the performance of hate comments discrimination. Smart Media Journal, 10(4), 71-79. http://10.30693/SMJ.2021.10.4.71
  8. Kim, Hyunguk & Song, Jinwoong (2020). Analysis of utilization and assessment of predicting models for YouTube science channel: focusing on using social big data analysis and machine learning. Journal of Educational Technology, 36(2), 383-412. http://10.17232/KSET.36.2.383
  9. KNU Korean Sentiment Lexicon Dictionary. Available: http://dilab.kunsan.ac.kr/knusl.html
  10. Kwon, Jae-Woong (2022). An analysis on Korean YouTube animation review channels. Cartoon & Animation Studies, 69, 301-342. http://10.7230/KOSCAS.2022.69.301
  11. Lee, Jin-hee, Kang, Myeong-bo, & Jeong, Yun-dong (2020). The effect of selection attributes of YouTube tourism channel on user satisfaction and intention to use. Tourism Research, 45(3), 365-382. http://10.32780/ktidoi.2020.45.3.365
  12. Lee, Jonghyun, Zang, HaiYun, & Choi, Jiho (2021). The differential effects of YouTube-Mediated intrinsic and extrinsic cues on attitude toward ad and tourist destination. Journal of Product Research, 39(6), 69-74. http://10.36345/kacst.2021.39.6.008
  13. Li, Yang & Lee, Jeong-ki (2023). A study on determinants of college students' intention to continue using audiobooks in Korea and China focusing on IMTBPT mode. Journal of Communication Science, 23(1), 137-181. http://10.14696/jcs.2023.03.23.1.137
  14. Ministry of Culture, Sports and Tourism (2024, April 18). 2023 National Reading Survey. Available: https://www.mcst.go.kr/kor/s_notice/notice/noticeView.jsp?pSeq=18001
  15. Park, Byung Eun & Lim, Gyoo Gun (2015). A study on the impact factors of contents diffusion in Youtube using integrated content network analysis. Journal of Intelligence and Information Systems, 21(3), 19-36. http://dx.doi.org/10.13088/jiis.2015.21.3.19
  16. Seo, Euna & Kim, Younjae (2021) A study on the preferred factors of audio content based on web novels: focusing on NAVER Audio Clips. Culture and Convergence, 43(11), 89-108. https://doi.org/10.33645/cnc.2021.11.43.11.89
  17. Sung, Haengnam & Lee, Taewon (2022). A study on the usage behavior of paid users in audio book platform: focused on the analysis of continuous use intention and market trends. The Journal of Internet Electronic Commerce Research, 22(3), 115-135. https://doi.org/10.37272/JIECR.2022.06.22.3.115
  18. Yi, Liu, Um, Myoung Yong, & Kim, Jai Beom (2023). The influence of the characteristics of Short-form content and recommendation system on Chinese users' flow and satisfaction: focusing on TikTok movie summary content. The e-Business Studies, 24(4), 91-109. https://doi.org/10.20462/TeBS.2023.8.24.4.91
  19. Yin, Yadong & Nam, Yoonjae (2021). A study on factors affecting intention to continue using mobile audiobook applications: based on the Expectation Confirmation Model, Technology Acceptance Model and Value-based Adoption Model. The Journal of Internet Electronic Commerce Research, 21(3), 127-144. https://doi.org/10.37272/JIECR.2021.06.21.3.127
  20. Aldous, K. K., An, J., & Jansen, B. J. (2019). View, Like, Comment, Post: Analyzing User Engagement by Topic at 4 Levels across 5 Social Media Platforms for 53 News Organizations, in Proceedings of the International AAAI Conference on Web and Social Media, 13(01), Munich: Germany, 47-57. https://doi.org/10.1609/icwsm.v13i01.3208
  21. Benson, P. (2017). YouTube as Text, in Discourse Analysis and Digital Practices Doing Discourse Analysis in the Digital Age, 1st ed. Oxon, OX: Routledge, Ch.6, 81-96.
  22. Emmons, S., Kobourov, S., Gallant, M., & Borner, K. (2016). Analysis of network clustering algorithms and cluster quality metrics at scale. PloS one, 11(7), e0159161. https://doi.org/10.1371/journal.pone.0159161
  23. Friedkin, N. E. (1991). Theoretical foundations for centrality measures. American Journal of Sociology, 96(6), 1478-1504. https://doi.org/10.1086/229694
  24. McGrady, R., Zheng, K., Curran, R., Baumgartner, J., & Zuckerman, E. (2023). Dialing for Videos: a random sample of YouTube. Journal of Quantitative Description: Digital Media, 3. https://doi.org/10.51685/jqd.2023.022
  25. Munaro, A. C., Barcelos, R. H., Francisco Maffezzolli, E. C., Santos Rodrigues, J. P., & Cabrera Paraiso, E. (2021). To engage or not engage? The features of video content on YouTube affecting digital consumer engagement. Journal of Consumer Behaviour, 20(5)5, 1336-1352. https://doi.org/10.1002/cb.1939
  26. Srivastava, N., Mishra, A., & Dwivedi, Y. K. (2022). Investigating antecedents of adoption intention for audiobook applications. Journal of Computer Information Systems, 62(4), 765-777. https://doi.org/10.1080/08874417.2021.1913672