Abstract
Through a computational reading of the online book reviewing community LibraryThing, we examine the dynamics of a collaborative tagging system and learn how its users refine and redefine literary genres. LibraryThing tags are overlapping and multi-dimensional, created in a shared space by thousands of users, including readers, bookstore owners, and librarians. A common understanding of genre is that it relates to the content of books, but this resource allows us to view genre as an intersection of user communities and reader values and interests. We explore different methods of computational genre measurement within the open space of user-created tags. We measure overlap between books, tags, and users, and we also measure the homogeneity of communities associated with genre tags and correlate this homogeneity with reviewing behavior.Finally, by analyzing the text of reviews, we identify the thematic signatures of genres on LibraryThing, revealing similarities and differences between them. These measurements are intended to elucidate the genre conceptions of the users, not, as in prior work, to normalize the tags or enforce a hierarchy. We find that LibraryThing users make sense of genre through a variety of values and expectations, many of which fall outside common definitions and understandings of genre.
- Peishan Bartley. 2009. Book tagging on LibraryThing: how, why, and what are in the tags? Proceedings of the American Society for Information Science and Technology, Vol. 46, 1 (2009), 1--22.Google Scholar
Cross Ref
- Douglas Biber. 1986. Spoken and written textual dimensions in English: Resolving the contradictory findings. Language (1986), 384--414.Google Scholar
- David M Blei, Andrew Y Ng, and Michael I Jordan. 2003. Latent Dirichlet allocation. JMLR, Vol. 3, Jan (2003), 993--1022.Google Scholar
Digital Library
- Karen Bourrier and Mike Thelwall. 2020. The Social Lives of Books: Reading Victorian Literature on Goodreads. Journal of Cultural Analytics (Feb. 2020), 12049. https://doi.org/10.22148/001c.12049Google Scholar
Cross Ref
- Amy Bruckman. 2002. Studying the amateur artist: A perspective on disguising data collected in human subjects research on the Internet. Ethics and Information Technology, Vol. 4, 3 (2002), 217--231.Google Scholar
Digital Library
- Tiago Cunha, David Jurgens, Chenhao Tan, and Daniel Romero. 2019. Are All Successful Communities Alike? Characterizing and Predicting the Success of Online Communities. In The World Wide Web Conference (San Francisco, CA, USA) (WWW '19). Association for Computing Machinery, New York, NY, USA, 318--328. https://doi.org/10.1145/3308558.3313689Google Scholar
Digital Library
- Cristian Danescu-Niculescu-Mizil, Robert West, Dan Jurafsky, Jure Leskovec, and Christopher Potts. 2013. No Country for Old Members: User Lifecycle and Linguistic Change in Online Communities. In Proceedings of the 22nd International Conference on World Wide Web (Rio de Janeiro, Brazil) (WWW '13). Association for Computing Machinery, New York, NY, USA, 307--318. https://doi.org/10.1145/2488388.2488416Google Scholar
Digital Library
- Tshering Dema, Margot Brereton, Jessica L. Cappadonna, Paul Roe, Anthony Truskinger, and Jinglan Zhang. 2017. Collaborative Exploration and Sensemaking of Big Environmental Sound Data. Comput. Supported Coop. Work, Vol. 26, 4--6 (Dec. 2017), 693--731. https://doi.org/10.1007/s10606-017-9286-9Google Scholar
Digital Library
- Brianna Dym and Casey Fiesler. 2020. Ethical and privacy considerations for research using online fandom data. Transformative Works and Cultures, Vol. 33 (2020).Google Scholar
Cross Ref
- James F. English, Scott Enderle, and Rahul Dhakecha. 2022. Bad Habits on Goodreads?. In In preparation for James F. English and Heather Love, eds., Literary Studies and Human Flourishing (New York). Oxford UP.Google Scholar
- Melanie Feinberg. 2013. Beyond Digital and Physical Objects: The Intellectual Work as a Concept of Interest for HCI. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 3317--3326. https://doi.org/10.1145/2470654.2466453Google Scholar
Digital Library
- Casey Fiesler and Nicholas Proferes. 2018. ?Participant" Perceptions of Twitter Research Ethics. Social Media +Society, Vol. 4 (2018).Google Scholar
- Stanley Fish. 1982. Is There a Text in This Class? The Authority of Interpretive Communities. Harvard University Press, Cambridge Mass.Google Scholar
- John Frow. 2014. Genre. Routledge.Google Scholar
- Scott A Golder and Bernardo A Huberman. 2006. Usage patterns of collaborative tagging systems. Journal of Information Science, Vol. 32, 2 (2006), 198--208.Google Scholar
Digital Library
- Jane Gruning. 2018. Displaying Invisible Objects: Why People Rarely Re-Read E-Books. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1--12. https://doi.org/10.1145/3173574.3173713Google Scholar
Digital Library
- William L Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, and Jure Leskovec. 2017. Loyalty in online communities. In Eleventh International AAAI Conference on Web and Social Media.Google Scholar
Cross Ref
- Paul Heymann, Andreas Paepcke, and Hector Garcia-Molina. 2010. Tagging Human Knowledge. In Proceedings of the Third ACM International Conference on Web Search and Data Mining (New York, New York, USA) (WSDM '10). Association for Computing Machinery, New York, NY, USA, 51--60. https://doi.org/10.1145/1718487.1718495Google Scholar
Digital Library
- Sudipta Kar, Suraj Maharjan, A. Pastor López-Monroy, and Thamar Solorio. 2018. MPST: A Corpus of Movie Plot Synopses with Tags. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). European Language Resources Association (ELRA), Miyazaki, Japan. https://www.aclweb.org/anthology/L18--1274Google Scholar
- Brett Kessler, Geoffrey Nunberg, and Hinrich Schutze. 1997. Automatic Detection of Text Genre. In 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, Madrid, Spain, 32--38. https://doi.org/10.3115/976909.979622Google Scholar
- Evgeny Kim, Sebastian Padó, and Roman Klinger. 2017. Investigating the Relationship between Literary Genres and Emotional Plot Development. In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Association for Computational Linguistics, Vancouver, Canada, 17--26. https://doi.org/10.18653/v1/W17-2203Google Scholar
Cross Ref
- Christian Körner, Dominik Benz, Andreas Hotho, Markus Strohmaier, and Gerd Stumme. 2010. Stop Thinking, Start Tagging: Tag Semantics Emerge from Collaborative Verbosity. In Proceedings of the 19th International Conference on World Wide Web (Raleigh, North Carolina, USA) (WWW '10). Association for Computing Machinery, New York, NY, USA, 521--530. https://doi.org/10.1145/1772690.1772744Google Scholar
Digital Library
- TK Landauer. 1984. Statistical semantics-analysis of the potential performance of keyword information-systems, and a cure for an ancient problem. In Journal of psycholinguistic research, Vol. 13. PLENUM PUBL CORP 233 SPRING ST, NEW YORK, NY 10013, 495--496.Google Scholar
- Suraj Maharjan, Manuel Montes, Fabio A. González, and Thamar Solorio. 2018. A Genre-Aware Attention Model to Improve the Likability Prediction of Books. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, Brussels, Belgium, 3381--3391. https://doi.org/10.18653/v1/D18--1375Google Scholar
Cross Ref
- Suman Kalyan Maity, Ayush Kumar, Ankan Mullick, Vishnu Choudhary, and Animesh Mukherjee. 2018. Understanding Book Popularity on Goodreads. In Proceedings of the 2018 ACM Conference on Supporting Groupwork (Sanibel Island, Florida, USA) (GROUP '18). Association for Computing Machinery, New York, NY, USA, 117--121. https://doi.org/10.1145/3148330.3154512Google Scholar
Digital Library
- Lynne M. Markus. 2001. Toward a theory of knowledge reuse: Types of knowledge reuse situations and factors in reuse success. Journal of Management Information Systems, Vol. 18, 1 (2001), 57--93.Google Scholar
Digital Library
- Julian John McAuley and Jure Leskovec. 2013. From Amateurs to Connoisseurs: Modeling the Evolution of User Expertise through Online Reviews. In Proceedings of the 22nd International Conference on World Wide Web (Rio de Janeiro, Brazil) (WWW '13). Association for Computing Machinery, New York, NY, USA, 897--908. https://doi.org/10.1145/2488388.2488466Google Scholar
Digital Library
- National Endowment for the Arts. 2004. Reading at Risk: A Survey of Literary Reading in America.Google Scholar
- Thomas Pavel. 2003. Literary Genres as Norms and Good Habits. New Literary History, Vol. 34, 2 (2003), 201--210. https://www.jstor.org/stable/20057776Google Scholar
Cross Ref
- Peter Pirolli. 2005. Rational analyses of information foraging on the web. Cognitive Science, Vol. 29, 3 (2005), 343--373.Google Scholar
Cross Ref
- J. D. Porter. 2018. Popularity/Prestige. Stanford Literary Lab, Vol. Pamphlet 17 (2018).Google Scholar
- Emilee Rader and Rick Wash. 2008. Influences on Tag Choices in Del.Icio.Us. In Proceedings of the 2008 ACM Conference on Computer Supported Cooperative Work (San Diego, CA, USA) (CSCW '08). Association for Computing Machinery, New York, NY, USA, 239--248. https://doi.org/10.1145/1460563.1460601Google Scholar
Digital Library
- Janice A. Radway. 1991. Reading the Romance: Women, Patriarchy, and Popular Literature .The University of North Carolina Press, Chapel Hill.Google Scholar
- Jeremy Rosen. 2018. Literary Fiction and the Genres of Genre Fiction. Post45: Peer-Reviewed (Aug. 2018). http://post45.research.yale.edu/2018/08/literary-fiction-and-the-genres-of-genre-fiction/Google Scholar
- Tiago Santos, Florian Lemmerich, Markus Strohmaier, and Denis Helic. 2019. What's in a Review: Discrepancies Between Expert and Amateur Reviews of Video Games on Metacritic. Proc. ACM Hum.-Comput. Interact., Vol. 3, CSCW, Article 140 (Nov. 2019), bibinfonumpages22 pages. https://doi.org/10.1145/3359242Google Scholar
Digital Library
- K. Schmidt and I. Wagner. 2004. Ordering Systems: Coordinative Practices and Artifacts in Architectural Design and Planning. Computer Supported Cooperative Work (CSCW), Vol. 13 (2004), 349--408.Google Scholar
Digital Library
- Shilad Sen, Shyong K. Lam, Al Mamunur Rashid, Dan Cosley, Dan Frankowski, Jeremy Osterhouse, F. Maxwell Harper, and John Riedl. 2006. Tagging, Communities, Vocabulary, Evolution. In Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work (Banff, Alberta, Canada) (CSCW '06). Association for Computing Machinery, New York, NY, USA, 181--190. https://doi.org/10.1145/1180875.1180904Google Scholar
Digital Library
- Gene Smith. 2007. Tagging: people-powered metadata for the social web .New Riders.Google Scholar
- Efstathios Stamatatos, Nikos Fakotakis, and George Kokkinakis. 2000. Automatic Text Categorization In Terms Of Genre and Author. Computational Linguistics, Vol. 26, 4 (2000), 471--495. https://www.aclweb.org/anthology/J00-4001Google Scholar
Digital Library
- Susan Leigh Star. 1989. The Structure of Ill-Structured Solutions: Boundary Objects and Heterogeneous Distributed Problem Solving. In Distributed Artificial Intelligence .Google Scholar
- Susan Leigh Star. 2010. This is Not a Boundary Object: Reflections on the Origin of a Concept. Science, Technology, & Human Values, Vol. 35 (2010), 601--617.Google Scholar
Cross Ref
- Eswaran Subrahmanian, Ira Monarch, Suresh Konda, Helen Granger, Russ Milliken, Arthur Westerberg, and The N-Dim Group. 2003. Boundary Objects and Prototypes at the Interfaces of Engineering Design. Comput. Supported Coop. Work, Vol. 12, 2 (May 2003), 185--203. https://doi.org/10.1023/A:1023976111188Google Scholar
- Chenhao Tan. 2018. Tracing community genealogy: how new communities emerge from the old. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 12.Google Scholar
- Jaime Teevan, Christine Alvarado, Mark S. Ackerman, and David R. Karger. 2004. The Perfect Search Engine is Not Enough: A Study of Orienteering Behavior in Directed Search. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vienna, Austria) (CHI '04). Association for Computing Machinery, New York, NY, USA, 415--422. https://doi.org/10.1145/985692.985745Google Scholar
- Laure Thompson and David Mimno. 2018. Authorless Topic Models: Biasing Models Away from Known Structure. In Proceedings of the 27th International Conference on Computational Linguistics. Association for Computational Linguistics, Santa Fe, New Mexico, USA, 3903--3914. https://www.aclweb.org/anthology/C18--1329Google Scholar
- William E. Underwood. 2016. The Life Cycles of Genres. Journal of Cultural Analytics (May 2016), 11061. https://culturalanalytics.org/article/11061-the-life-cycles-of-genresGoogle Scholar
Cross Ref
- Thomas Vander Wal. 2005. Folksonomy Definition and Wikipedia. http://www.vanderwal.net/random/entrysel.php?blog=1750Google Scholar
- Thomas Vander Wal. 2007. Folksonomy. https://www.vanderwal.net/essays/051130/folksonomy.pdfGoogle Scholar
- Melanie Walsh and Maria Antoniak. 2021. The Goodreads "Classics": A Computational Study of Readers, Amazon, and Crowdsourced Amateur Criticism. Post45 and Journal of Cultural Analytics (2021).Google Scholar
- Mengting Wan and Julian J. McAuley. 2018. Item recommendation on monotonic behavior chains. In Proceedings of the 12th ACM Conference on Recommender Systems, RecSys 2018, Vancouver, BC, Canada, October 2-7, 2018,, Sole Pera, Michael D. Ekstrand, Xavier Amatriain, and John O'Donovan (Eds.). ACM, 86--94. https://doi.org/10.1145/3240323.3240369Google Scholar
- Mengting Wan, Rishabh Misra, Ndapa Nakashole, and Julian McAuley. 2019. Fine-Grained Spoiler Detection from Large-Scale Review Corpora. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, 2605--2610. https://doi.org/10.18653/v1/P19--1248Google Scholar
Cross Ref
- Jianling Wang, Ziwei Zhu, and James Caverlee. 2020. User Recommendation in Content Curation Platforms. In Proceedings of the 13th International Conference on Web Search and Data Mining. 627--635.Google Scholar
Digital Library
- Rick Wash and Emilee Rader. 2007. Public bookmarks and private benefits: An analysis of incentives in social computing. Proceedings of the American Society for Information Science and Technology, Vol. 44, 1 (2007), 1--13.Google Scholar
Cross Ref
- Jonathan Weber. 2006. Folksonomy and controlled vocabulary in LibraryThing. Unpublished Final Project, University of Pittsburgh (2006), 5--6.Google Scholar
- Matthew Wilkens. 2016. Genre, Computation, and the Varieties of Twentieth-Century U.S. Fiction. Journal of Cultural Analytics (1 11 2016).Google Scholar
- Adam Worrall. 2015. "Like a Real Friendship": Translation, Coherence, and Convergence of Information Values in LibraryThing and Goodreads. iConference 2015 Proceedings (2015).Google Scholar
- Joseph Worsham and Jugal Kalita. 2018. Genre Identification and the Compositional Effect of Genre in Literature. In Proceedings of the 27th International Conference on Computational Linguistics. Association for Computational Linguistics, Santa Fe, New Mexico, USA, 1963--1973. https://www.aclweb.org/anthology/C18-1167Google Scholar
- Diyi Yang, Robert E. Kraut, Tenbroeck Smith, Elijah Mayfield, and Dan Jurafsky. 2019. Seekers, Providers, Welcomers, and Storytellers: Modeling Social Roles in Online Health Communities. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19). ACM, New York, NY, USA, Article 344, bibinfonumpages14 pages. https://doi.org/10.1145/3290605.3300574Google Scholar
Digital Library
- Justine Zhang, William L Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, and Jure Leskovec. 2017. Community identity and user engagement in a multi-community landscape. In Eleventh International AAAI Conference on Web and Social Media.Google Scholar
Cross Ref
- Arkaitz Zubiaga, Christian Körner, and Markus Strohmaier. 2011. Tags vs Shelves: From Social Tagging to Social Classification. In Proceedings of the 22nd ACM Conference on Hypertext and Hypermedia (Eindhoven, The Netherlands) (HT '11). Association for Computing Machinery, New York, NY, USA, 93--102. https://doi.org/10.1145/1995966.1995981Google Scholar
Digital Library
Index Terms
Tags, Borders, and Catalogs: Social Re-Working of Genre on LibraryThing
Recommendations
Automatic tag expansion using visual similarity for photo sharing websites
In this paper we present an automatic photo tag expansion method designed for photo sharing websites. The purpose of the method is to suggest tags that are relevant to the visual content of a given photo at upload time. Both textual and visual cues are ...
Tag navigation
SoSEA '09: Proceedings of the 2nd international workshop on Social software engineering and applicationsThe amount of information available on the world wide web keeps growing at an exponential pace. Social tagging is a feature of various online social networks to organize information elements by letting people label these with free-form text, called ...
Content-Based Tag Generation for the Grouping of Tags
ELML '09: Proceedings of the 2009 International Conference on Mobile, Hybrid, and On-line LearningA tagging system can encounter too few or too many tags. To solve these problems, we propose a content-based automatic generation of tags. Applied to an e-Learning 2.0 application, the proposal creates tags based on lecture slide contents, generating an ...






Comments