[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-150845-en":3,"doc-seo-150845-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},150845,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","Facet Analysis of Anime Genres - The Challenges of Defining Genre Information for Popular Cultural Objects","Anime is a fast-growing multimedia form whose terminology needs stronger organization to support discovery. Existing research shows that patrons want to search and receive recommendations, yet indexing gaps and inconsistent or inaccurate term usage hinder effective access. The study performs facet analysis of anime genre terms from 36 English-language databases and websites using inductive card sorting, identifying nine facets and 153 focus terms to improve genre definitions and search experiences.","Knowl. Org. 47(2020)No.1  \nH. Cho, Th. Disher, W.-C. Lee, S. A. Keating and J. H. Lee. Facet Analysis of Anime Genres  \n13  \nFacet Analysis of Anime Genres: The Challenges of Defining Genre Information  \nfor Popular Cultural Objects†  \nHyerim Cho*, Thomas Disher**, Wan-Chen Lee***, Stephen A. Keating**** and Jin Ha Lee*****  \n*University of Missouri, 303 Townsend Hall, 221K, Columbia, MO 65211, USA, \u003C[hyerimcho@missouri.edu](hyerimcho@missouri.edu) >  \n***University of Washington, Information School, Mary Gates Hall, Suite 370, Box 352840, Seattle, WA 98195, USA, \u003C[leew23@uw.edu](leew23@uw.edu) >,  \n****1201 Elm Forest Drive, Cedar Park, TX 78613, USA, \u003C [stephen@ettugamer.com](stephen@ettugamer.com) >**, *****University of Washington, Information School, Mary Gates Hall 330Y-2 Gamer Lab,  \n1851 NE Grant Ln., Seattle, WA 98105, USA,  \n**\u003C[tdisher@uw.edu](tdisher@uw.edu) >, *****\u003C[jinhalee@uw.edu](jinhalee@uw.edu) >  \nHyerim Cho earned her PhD in information science from the University of Washington. Focusing on users, her research investigates diverse multimedia and pop-cultural information based on information science and media studies to provide enhanced recommendation and retrieval services. Her research interests include information needs and behavior, metadata, qualitative studies and mixed methods, and visual narrative materials such as graphic novels, anime, and video games.  \n\n| Thomas Disher is a writer and stay-at-home-father. He holds a BA in English creative writing, with a linguistics minor from Seattle Pacific University and a MLIS from the University of Washington. Since earning his MLIS he has assisted Jin Ha Lee and the GAMER group with some of their research at the University of Washington. His research interests include metadata, classification systems, video games, anime, folklore, and linguistics. He also writes poetry and fiction. |\n| --- |\n| Wan-Chen Lee is a PhD candidate at the Information School of the University of Washington, where she received her MLIS degree in 2014. She holds a BA in LIS from National Taiwan University. Her research interests include knowledge organization, classification theory, culture and classification, globalization and localization of cataloging and classification standards, and metadata. |\n\nStephen Keating is a Senior User Researcher with Dell, with a master’s in information science from the University of Washington, and a master’s in media studies from The New School. Research interests include information organization, metadata, and semantic analysis, as well as a particular focus on the preservation of digital ephemera.  \nJin Ha Lee is Associate Professor at the University of Washington’s Information School and the director of the GAMER (GAME Research) Group. Her research interests include music, anime, game and multimedia information seeking and retrieval, information organization and access, and knowledge representation. The GAMER Group explores new ideas and approaches for organizing and providing access to video games and other multimedia, understanding user behavior related to these media, and using them for informal learning. She holds an MS (2002) and a PhD (2008) from the University of Illinois at Urbana-Champaign.  \nCho, Hyerim, Thomas Disher, Wan-Chen Lee, Stephen A. Keating and Jin Ha Lee. 2020.“Facet Analysis of Anime Genres: The Challenges of Defining Genre Information for Popular Cultural Objects.” Knowledge Organ  \nization 47(1): 13-30. 50 references. DOI:10.5771/0943-7444-2020-1-13 .  \nAbstract: Anime, as a growing form of multimedia, needs a better and more thorough organization for its myriad unique terminologies. Existing studies show patrons’desire to search and get recommendations for anime. However, due to inadequate indexing and often confusing or inaccurate usage of terms, searching and acquiring recommendations remain challenging. Our research seeks to close the gap and  \n[https://doi.org/10.5771/0943-7444-2020-1-13](https://doi.org/10.5771/0943","cbCairEQB2RvvY9M","https://ap.wps.com/l/cbCairEQB2RvvY9M","pdf",522919,1,18,"English","en",105,"# Introduction\n## Research objective and gap\n## Data sources and term collection\n## Method: card sorting and inductive analysis\n## Findings: facets and focus terms\n## Applications for discovery and recommendations","[{\"question\":\"Why is defining anime genre information difficult for libraries and recommendation systems?\",\"answer\":\"Searching and recommendations are challenging due to inadequate indexing and confusing or inaccurate usage of genre terms.\"},{\"question\":\"What method does the study use to analyze anime genre terminology?\",\"answer\":\"It conducts facet analysis using a card sorting method with an inductive approach applied to 1,597 collected terms.\"},{\"question\":\"What outputs does the research produce from the facet analysis?\",\"answer\":\"The study identifies and defines nine facets and 153 focus terms describing different genres of anime.\"}]","Facet Analysis of Anime Genres - 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