1. Analysis of Social Tagging and Book Cataloging: A Case Study Yi-Chen Chen 陳怡蓁 Dept. of Library & Information Science National Taiwan University HKLA 50th Anniversary Conference Hong Kong, 5 November 2008

2. Outline Introduction ▫ Background + Related Work Research Questions Data and Methodology Results Conclusions and Future Directions

3. Background the concept of social tagging has grown in popularity on the web-based services it is quite different from controlled vocabularies-based indexing or authority- based cataloging (Mathes, 2004; Guy & Tonkin, 2006) the emergence of social tagging has begun to challenge traditional ways of information organization

4. Related Works… the difference between social tagging and traditional cataloging/indexing has been noticed (Tennis, 2006), but very few of the studies were conducted to verify it little research has been performed to examine how social tagging is applied to resources of books ▫ since the resources (books) are already catalogued with library subject headings

5. In this study…

6. Objective & purposes discover the properties and functions of social tags attached to books compare user-created tags with authoritative subject headings

7. Case study… A case study on LibraryThing’s tagging system ▫ “an online service to help people catalog their books easily” ▫ allows its members to add tags for their personal book collections

9. Research Questions How can tags be organized or classified into different function types? What kinds of function tags are most often used? How are tagging terms similar to or different from library subject headings?

10. Two parts of our studies Part 1  investigate functions of tags and derives a classification based on the types of functions  explore what kinds of tag classes are more popular among users Part 2  compare social tags with LCSH assigned to the same works of books and examine their overlaps and variations

11. Part 1: Analysis of classifying tags and usage frequency

12. Data collection LibrayThing (http://www.librarything.com) is chosen as our platform for data collection and analysishttp://www.librarything.com The data we used for this study was gathered from LibraryThing in July 2008.

13. Data collection sample of books including both fiction and non-fiction works ▫ randomly selected from the “Most often tagged fiction” and “Most often tagged non-fiction” booklist in LibraryThing ▫ two criteria: (1) English books; (2) the corresponding catalog records should include LCSH.

14. Data collection total number of works = 50 25 fiction + 25 non-fiction

15. Part 1: Methodology extract the tagging data (tag cloud and tag frequency) from these 50 works main page tag cloud only use the main page tag cloud for analysis ▫ a tag cloud that appear on the main page for each work includes only the top frequency tags

17.  the tag frequency data was gathered on the tag cloud of each work, indicating how many times the tag was used for a particular work

18. In total, there are 2,249 tags associated with the selected works, and 45 tags per work on average Number of tags TotalAverage (per work) Fiction114245.68 Non-fiction110744.28 All works224944.98

19. Part 1: Results( Ⅰ ) For these 2,249 tags, we analyze their function types and classified them. Classification framework for tags was created

20. ClassSubclass 1. Bibliographic Description Genre/Form Author Country of origin Language Edition Variant formats Audience 2. Subject-related Character/People Timeframe Setting/Place Topic Subject area 3. Personal reference Ownership Reading Progress Time Task Location 4. Opinion 5. Awards/Top list 6. Community

21. 1. Bibliographic description  describe physical attributes of the work and can give factual information about the book Genre/Form (e.g. “science fiction” ) Author Country of origin Edition (e.g. “first edition”) Variant formats (e.g. “film”) Audience (e.g. “kids”)

22. 2. Subject-related  tags that intended to reflect what a work is about and deal with the content of the resource abstract and concrete concepts, things or objects, subject areas, character names, settings or place, timeframe of the story, themes of the document, topics and the like

23. 3. Personal reference  act as reminders to oneself based on his/her personal context Ownership (e.g. “borrowed”) Reading Progress (e.g. “unread”, “tbr”) Time (e.g. “2007”) Task (e.g. “@work”, “textbook”) Location (e.g. “bookshelf”)

24. 4. Opinion users can express their feelings and opinion about the resource with tags subjectively reveal the reader’s value judgments and emotional reaction to a particular book (e.g. “favorite”, “interesting”)

25. 5. Awards/Top list a specific award or prize name (e.g. “Pulitzer prize”, “Nobel prize”) the top book list (e.g. “1001books”)

26. 6. Community apply such tags to the books that they wish to share or discuss with others convey the community meaning of the resource (e.g. “book club”)

27. Part 1: Results Distribution of number of tags Distribution of tag frequency

28. Part 1: Results Distribution of number of tags Distribution of tag frequency

29. Number of tags (all works)

30. Bibliographic description Genre/Form

31. Personal reference Reading Progress

32. Number of tags (fiction)

33. Number of tags (non-fiction)

34. Part 1: Results Distribution of number of tags Distribution of tag frequency

35. Part 1: Results Distribution of number of tags Distribution of tag frequency ▫ investigate if certain tag classes are used more frequently than others

36. Tag frequency (all works)

37. Tag frequency (fiction)

38. Tag frequency (non-fiction)

39. Part 1: Results & Findings users are more likely to distinguish fiction works by their genre or form, and distinguish non-fiction works by their subject of books

40. Number of tags vs. Tag frequency ? Although Subject-related has the largest number of tags among all the works, its tag usage frequency is not as high as that of Bibliographic description. vs. Subject-related Bibliographic description

41. Part 1: Results & Findings number of tags vs. tag usage frequency ? the subject matter could be divergent and expressed in a variety of words, so its tag usage frequency is lower the descriptions of bibliographic data often have common usage, especially of genre/form, thus resulting in clear convergence on the tagging terms

42. Part 2: Comparison of social tags and LCSH terms

43. Part 2: Methodology Dataset the Bibliographic description tags and Subject-related tags (from part 1) the subject headings data was extracted from the LCSH terms assigned to each selected work in Library of Congress Online Catalogs (http://catalog.loc.gov/webvoy.htm)

45. Part 2: Methodology subject heading string may comprise the main headings and dash-subdivisions with complicated combinations (e.g. Japan --History --20th century --Fiction) we separated the combination of subject headings into several concept terms and excluded the duplicate terms. (e.g. Japan. History. 20th century. Fiction.)

46. Part 2: Preliminary results 1,759 tags (Bibliographic description and Subject-related tags) 35.2 tags per work 313 LCSH terms 6.3 LCSH terms per work

47. Rules of comparison (1) tags and LCSH terms associated with the same work are compared in a term-by-term manner. (2) the overlap is identified with an exact or almost exact match in spelling, including plural/singular forms and case variations. (3) abbreviations or acronyms are considered the same as the full form of terms. (4) preposition, punctuation mark and symbol are ignored.

48. Overlaps between tags and LCSH Tags LCSH terms Overlapped tags tags not covered in SH (Non-overlap) tags not covered in SH (Non-overlap)

49. All works Tags (1759) LCSH (313) 10.8% (overlap)

50. Fiction… Tags (895) LCSH (163) 10.2% (overlap) 10.2% (overlap)

51. Non-fiction… Tags (864) LCSH (150) 11.5% (overlap) 11.5% (overlap)

52. Tags vs. LCSH terms how the rest of 90% non-overlapped tags are different from the LCSH terms? ▫ not reflected in library subject headings

53. Compared with LCSH, Tags … more genre/form information describe more character names in the content of books simpler and informal usage on personal names, geographic names, and timeframe Tag: “classic fiction”, “Thriller”, “historical fiction” LCSH: “Fiction” Tag: “da vinci” LCSH: “Leonardo, da Vinci, 1452-1519” Tag: ““Delft” LCSH: “Delft (Netherlands)” Tag: “1920s” LCSH: “Alfonso XIII, 1886-1931”

54. the syntax of LCSH… multi-concepts phrases (e.g. “Good and evil”) subject headings can be with qualifiers to distinguish between homographs or to avoid ambiguity inverted headings (e.g. “Cookery, French”)  rarely used in social tagging

55. Non-overlapped tags (three types) (1)terms with identical meanings, but different words or different grammatical forms (2)variations of broader terms, narrower terms, and related terms (3)terms expressing extra concepts  different ways of representing the concepts and the semantic relationships among terms  the different interpretation in subject analysis between users and library catalogers

56. Part 2: Findings Compared to the subject headings, these non- overlapped tags appear to be more exhaustive of the topics covered in a resource the non-overlapped tags, especially those terms with extra concepts, describe more themes or topics covered by the content of a book

57. Conclusions

58. Reorganizing and classifying tags our classification framework is intended to unveil the functions of tags applied to books understand how a book/item is described and identified by users in bibliographic records reorganize tags into classes to improve the user experience of searching and browsing

59. Subject cataloging and social tags the relatively low degree of overlaps between tags and LCSH tags provide a richer description of the book’s subject matter higher exhaustivity using tags supplement existing controlled vocabularies such as subject description

60. Future Directions the classification framework for tags needs further evaluation to prove its usefulness and applicability of book cataloging the rules of comparison between tags and LCSH still need to be discussed study the overlapped and non-overlapped subject terms more comprehensively semantic issue…

61. Thank you! Comments & Suggestions

63. Acknowledgments The author would like to thank Dr. Muh-Chyun Tang and Dr. Kuang-hua Chen for their helpful comments.

64. References Begelman, G., Keller, P. and Smadja, F. (2006). Automated Tag Clustering: Improving search and exploration in the tag space. Paper presented at the WWW2006 Collaborative Tagging Workshop. Available online: http://www.pui.ch/phred/automated_tag_clustering/ http://www.pui.ch/phred/automated_tag_clustering/ Brooks, C. H. & Montanez, N. (2006, May). Improved annotation of the blogosphere via autotagging and hierarchical clustering. In Proceedings of the 15th International Conference on World Wide Web (pp. 625-632). New York: ACM Press. Furner, J. (2007). User tagging of library resources:Toward a framework for system evaluation. Paper presented at the 157 Classification and Indexing. Available online: http://www.ifla.org/iv/ifla73/index.htm. http://www.ifla.org/iv/ifla73/index.htm Golder, S. A., & Huberman, B. A. (2006). Usage patterns of collaborative tagging systems. Journal of Information Science, 32(2), 198-208. Guy, M., & Tonkin, E. (2006). “Folksonomies: Tidying up Tags?” D-Lib Magazine, 12(1). Heckner, M., Mühlbacher, S.,and Wolff, C. (2008). Tagging tagging. Analysing user keywords in scientific bibliography management systems. Journal of Digital Information, 9(27). Kipp, M. E. & Campbell, D. G. (2006, November). Patterns and Inconsistencies in Collaborative Tagging Practices: An Examination of Tagging Practices. Paper presented at Proceedings of the Annual General Meeting of the American Society for Information Science and Technology, Austin, TX.

65. Kipp, M. E. (2006). Complementary or Discrete Contexts in Online Indexing: A Comparison of User, Creator, and Intermediary Keywords. Canadian Journal of Information and Library Science, 30(3). Retrieved June 18, 2008, from: http://dlist.sir.arizona.edu/1533/ http://dlist.sir.arizona.edu/1533/ Kipp, M. E. (2007). @toread and Cool: Tagging for Time, Task and Emotion. In Proceedings 8th Information Architecture Summit, Las Vegas, Nevada, USA. Macgregor, G. & McCulloch, E. (2006). Collaborative tagging as a knowledge organisation and resource discovery tool. Library Review, 55(5), 291–300. Mai, J.-E. (2005). Analysis in indexing: Document and domain centered approaches. Information Processing & Management, 41, 599-611. Marlow, C., Naaman, M., Boyd, D., and Davis, M. (2006). HT06, tagging paper, taxonomy, Flickr, academic article, to read. In: U.K. Wiil et al. (eds), Proceedings of the 17th Conference on Hypertext and Hypermedia (pp. 31–39). ACM, New York. Mathes, A. (2004). Folksonomies - Cooperative Classification and Communication Through Shared Metadata. Olson, H. A., & Boll, J. J. (2001). Subject Analysis in Online Catalogs. Englewood, Colo: Libraries Unlimited. Quintarelli, E., Resmini, A., and Rosati L. (2007). FaceTag: integrating bottom-up and top-down classification in a social tagging system. Paper presented at International IA Summit 2007, Las Vegas, Nevada, United States. Available online: http://www.facetag.org/download/facetag-20070325.pdf http://www.facetag.org/download/facetag-20070325.pdf

66. Sauperl, A. (2004). Catalogers’ common ground and shared knowledge. Journal of the American Society for Information Science and Technology, 55, 55-63. Sen, S., Lam, S. K., Rashid, A. M., Cosley, D., Frankowski, D., Osterhouse, J., Harper, F. M., and Riedl, J. (2006). Tagging, communities, vocabulary, evolution. In Proceedings of CSCW 2006, Banff, Alberta, Canada. Shirky, Clay (2005). Ontology is Overrated: Categories, Links, and Tags. Retrieved 16 November 2007, from: http://shirky.com/writings/ontology_overrated.htmlhttp://shirky.com/writings/ontology_overrated.html Sinclair, J. & Cardew-Hall, M. (2008). The folksonomy tag cloud: when is it useful? Journal of Information Science, 34 (1), 15–29. Spiteri, L. F. (2007). Structure and form of folksonomy tags: The road to the public library catalogue. Webology, 4(2). Retrieved June 18, 2008, from: http://www.webology.ir/2007/v4n2/a41.html http://www.webology.ir/2007/v4n2/a41.html Tennis, J. (2006). Social tagging and the next steps for indexing. Paper presented at the 17th Annual SIG/CR Classification Research Workshop, Austin, TX. Voß, J. (2007). Tagging, Folksonomy & Co - Renaissance of Manual Indexing? Retrieved December 19, 2007, from: http://arxiv.org/abs/cs/0701072v2http://arxiv.org/abs/cs/0701072v2 Weinberger, D. (2005). Tagging and Why It Matters. Retrieved November 7, 2007, from: http://cyber.law.harvard.edu/home/uploads/507/07-WhyTaggingMatters. http://cyber.law.harvard.edu/home/uploads/507/07-WhyTaggingMatters