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리뷰 정보를 활용한 이용자의 선호요인 식별에 관한 연구

Identification of User Preference Factor Using Review Information

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참고문헌

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주제분류문헌정보학

초록

본 연구는 도서관 정보서비스 환경에서 도서 이용자의 도서추천에 영향을 미치는 선호요인을 파악하기 위해 전 세계 도서 이용자의 참여로 이루어지는 사회적 목록 서비스인 Goodreads 리뷰 데이터를 대상으로 내용분석하였다. 이용자 선호의 내용을 보다 세부적인 관점에서 파악하기 위해 샘플 선정 과정에서 평점 그룹별, 도서별, 이용자별 하위 데이터 집합을 구성하였으며, 다양한 토픽을 고루 반영하기 위해 리뷰 텍스트의 토픽모델링 결과에 기반하여 층화 샘플링을 수행하였다. 그 결과, ‘내용’, ‘캐릭터’, ‘글쓰기’, ‘읽기’, ‘작가’, ‘스토리’, ‘형식’의 7개 범주에 속하는 총 90개 선호요인 관련 개념을 식별하는 한편, 평점에 따라 드러나는 일반적인 선호요인은 물론 호불호가 분명한 도서와 이용자에서 드러나는 선호요인의 양상을 파악하였다. 본 연구의 결과는 이용자 선호요인의 구체적 양상을 파악하여 향후 추천시스템 등에서 보다 정교한 추천에 기여할 수 있을 것으로 보인다.

Abstract

This study analyzed the contents of Goodreads review data, which is a social cataloging service with the participation of book users around the world, to identify the preference factors that affect book users’ book recommendations in the library information service environment. To understand user preferences from a more detailed point of view, sub-datasets for each rating group, each book, and each user were constructed in the sample selection process. Stratified sampling was also performed based on the result of topic modeling of review text data to include various topics. As a result, a total of 90 preference factors belonging to 7 categories(‘Content’, ‘Character’, ‘Writing’, ‘Reading’, ‘Author’, ‘Story’, ‘Form’) were identified. Also, the general preference factors revealed according to the ratings, as well as the patterns of preference factors revealed in books and users with clear likes and dislikes were identified. The results of this study are expected to contribute to more sophisticated recommendations in future recommendation systems by identifying specific aspects of user preference factors.

참고문헌 (40)

  1. 김라연, "독서 감상문의 구성 요소 분석 연구", 교육과학연구, 17, pp.17~30 (2011)
  2. 김성훈, "연관성분석 기반 도서추천서비스의 이용자 만족에 관한 내러티브 연구", 한국도서관·정보학회지, 52(3), pp.287~311 (2021), 한국도서관·정보학회[DOI]
  3. 박동진, "독서 감상문 쓰기의 실태 - 구성 요소 분석을 중심으로", 새국어교육, (84), pp.109~126 (2010), 한국국어교육학회[DOI]
  4. 변제연, "도서관 이용자 코멘트 데이터 분석도구 리뷰 및 적용: LibQUAL+ 설문 데이터를 중심으로", 정보관리학회지, 30(3), pp.157~181 (2013), 한국정보관리학회[DOI]
  5. 손은정, "이용자 로그데이터 기반 대학도서관 일반열람실 활용도 및 선호요인 분석 - J대학의 사례를 중심으로 -", 한국문헌정보학회지, 54(2), pp.375~398 (2020), 한국문헌정보학회[DOI]
  6. 심지영, "도서추천 시스템 개선을 위한 도서이용 맥락 요소 탐색", 정보관리학회지, 39(2), pp.299~324 (2022), 한국정보관리학회[DOI]
  7. 유다빈, "통합 리뷰 감정 분석을 통한 맞춤형 도서 비교 및 평가 시스템설계", 한국정보처리학회 학술대회논문집, 22(1), pp.108~111 (2015)
  8. 윤정옥, "차세대 도서관 목록의 이용자 서평에 관한 고찰", 한국문헌정보학회지, 46(2), pp.115~132 (2012), 한국문헌정보학회[DOI]
  9. 임정수, "최신 영화 VOD 이용자의 선호도에 대한 컨조인트 분석", 한국콘텐츠학회 논문지, 13(5), pp.191~198 (2013), 한국콘텐츠학회[DOI]
  10. 최지은, "리뷰 감정 분석을 통한 전자상거래 상품 분석 및 평가 시스템 설계", 정보과학회 컴퓨팅의 실제 논문지, 22(5), pp.209~217 (2016), 한국정보과학회
  11. Wendy Begay, "Quantifying qualitative data: using LibQUAL+ (™) comments for library-wide planning activities at the university of arizona", Journal of Library Administration, 40(3-4), pp.111~119 (2004), Informa UK Limited[DOI]
  12. Bhat, N. A., "Assessment of user preference to information resources in agricultural libraries in north India", Annals of Library and Information Studies, 65(2), pp.96~99 (2018)[DOI]
  13. Chen, L., "Recommender systems based on user reviews : the state of the art", User Modeling and User-Adapted Interaction, 25(2), pp.99~154 (2015)[DOI]
  14. "Public Library Groups" (2022)[URL]
  15. Green, P. E., "Conjoint analysis in marketing research : new developments and directions", Journal of Marketing, 54(4), pp.3~19 (1990)[DOI]
  16. Joulin, A., "Bag of tricks for efficient text classification", Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2, pp.427~431 (2017)
  17. Kadiresan, N., "Examining the relationship between academic book citations and Goodreads reader opinion and rating", Annals of Library and Information Studies, 67(4), pp.215~221 (2021)[DOI]
  18. Korfiatis, N., "Measuring service quality from unstructured data : a topic modeling application on airline passengers’ online reviews", Expert Systems with Applications, 116, pp.472~486 (2019)[DOI]
  19. Kousha, K., "Goodreads reviews to assess the wider impacts of books", Journal of the Association for Information Science and Technology, 68(8), pp.2004~2016 (2017)[DOI]
  20. Apple Hiu Ching Lam, "Instagram for student learning and library promotions: a quantitative study using the 5E Instructional Model", Aslib Journal of Information Management (2022), Emerald[DOI]
  21. Liu, H., "Combining user preferences and user opinions for accurate recommendation", Electronic Commerce Research and Applications, 12(1), pp.14~23 (2013)[DOI]
  22. Mariana, S., "Association rule mining for building book recommendation system in online public access catalog", Proceedings of the 2017 3rd International Conference on Science in Information Technology, pp.246~250 (2017)
  23. McNee, S. M., "Being accurate is not enough:how accuracy metrics have hurt recommender systems", Paper presented at the CHI'06extended abstracts on Human factors in computing systems, pp.1097~1110 (2006)
  24. Naik, Y., "Finding good reads on Goodreads : Readers take RA into their own hands", Reference and User Services Quarterly, 51(4), pp.319~323 (2012)
  25. Oded Netzer, "Beyond conjoint analysis: Advances in preference measurement", Marketing Letters, 19(3-4), pp.337~354 (2008), Springer Science and Business Media LLC[DOI]
  26. Park, S., "Usability, user preferences, effectiveness, and user behaviors when searching individual and integrated full-text databases : implications for digital libraries", Journal of the American Society for Information Science, 51(5), pp.456~468 (2000)[DOI]
  27. Qi, P., "Stanza: a python natural language processing toolkit for many human languages", Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp.101~108 (2020)
  28. Betsaida M. Reyes, "An assessment of e-book collection development practices among Romance language librarians", Collection and Curation, 40(1), pp.24~30 (2020), Emerald[DOI]
  29. M. Ryan, "Using conjoint analysis to elicit preferences for health care", BMJ, 320(7248), pp.1530~1533 (2000), BMJ[DOI]
  30. Shah, A. M., "What patients like or dislike in physicians : analyzing drivers of patient satisfaction and dissatisfaction using a digital topic modeling approach", Information Processing & Management, 58(3), pp.102516~ (2021)[DOI]
  31. Sohail, S. S., "Book Recommendation System Using Opinion Mining Technique", Paper presented at the 2013 International Conference on Advances in Computing, Communications and Informatics, pp.1609~1614 (2013)
  32. Sun, L., "Joint topic-opinion model for implicit feature extracting", Proceedings of 2015 10th International Conference on Intelligent Systems and Knowledge Engineering, pp.208~213 (2015)
  33. Mike Thelwall, "Goodreads: A social network site for book readers", Journal of the Association for Information Science and Technology, 68(4), pp.972~983 (2016), Wiley[DOI]
  34. Yun-Fang Tu, "Analysing reader behaviours in self-service library stations using a bibliomining approach", The Electronic Library, 39(1), pp.1~16 (2020), Emerald[DOI]
  35. Tubishat, M., "Implicit aspect extraction in sentiment analysis : review, taxonomy, oppportunities, and open challenges", Information Processing & Management, 54(4), pp.545~563 (2018)[DOI]
  36. Wan, M., "Fine-grained spoiler detection from large-scale review corpora", Proceedings of the 2019 57th Conference of the Association for Computational Linguistics, pp.2605~2610 (2019)
  37. Kelly Marie Wilson, "Comparing Print and eBook Usage to Meet Patron Needs", Collection Management, 46(2), pp.91~106 (2020), Informa UK Limited[DOI]
  38. Wu, D., "Comparing social tags with subject headings on annotating books : a study comparing the information science domain in English and Chinese", Journal of Information Science, 39(2), pp.169~187 (2013)[DOI]
  39. Wu, F., "Developing a novel recommender network-based ranking mechanism for library book acquisition", Electronic Library, 35(1), pp.50~68 (2017)[DOI]
  40. Xiao, S., "Crowd intelligence : analyzing online product reviews for preference measurement", Information & Management, 53(2), pp.169~182 (2016)[DOI]

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