ASIS&T 2006 Annual Meeting

SOCIAL CLASSIFICATION: PANACEA OR PANDORA?
17th Annual ASIS&T SIG/CR Classification Research Workshop Saturday, November 4, 2006 -- Austin, TX
Full Day Seminar, Saturday, Nov. 4, 2006, 8:30am-5:00pm (separate fee)

CALL FOR PARTICIPATION

IMPORTANT DATES
September 22, 2006: Deadline for early-bird registration ($105 for ASIS&T members, $120 for non-members) November 4, 2006: Day of workshop

OVERVIEW
Researchers, practitioners, and students interested in social classification, folksonomies, social tagging, social bookmarking, collaborative indexing, collaborative annotation, etc., are invited to participate in the 17th ASIS&T SIG/CR Classification Research Workshop. Attendees will have the opportunity to contribute to the debate by actively participating in the workshop's open panel sessions.

This workshop will be held at the Hilton Austin, 500 E 4th St, Austin, TX, from 8:30am to 5pm on Saturday, November 4, 2006, as part of the Annual Meeting of the Association for Information Science and Technology (ASIS&T). It will be the 17th in a series of annual workshops organized by ASIS&T's Special Interest Group on Classification Research (SIG/CR). Please see the main ASIS&T AM06 page at http://www.asis.org/Conferences/AM06/index.html for further general information about the ASIS&T Annual Meeting, including instructions on how to register for the SIG/CR Workshop using the online registration form at https://www.asis.org/Conferences/AM06/
am06regform.php. Please see http://www.slais.ubc.ca/USERS/sigcr/ for further information about SIG/CR. Preprints of the full papers, and abstracts of the posters, will shortly be available for download by workshop attendees from the SIG/CR website at http://www.slais.ubc.ca/ USERS/sigcr/pubs.html.

AGENDA
8:30 Coffee
9:00 Introduction
9:15 Keynote
10:15 Break
10:30 Panel 1: The Structure of Social Classification 12:00 1-Minute Madness, Poster Session, and Lunch
1:00 Panel 2: Discussion of Posters
1:30 Panel 3: Social Classification of Visual Resources
3:00 Break
3:15 Panel 4: Conceptual Frameworks for Social Classification
4:45 Wrap-Up

KEYNOTE
Tagging: It's the interface, stupid!
Joseph Busch (Taxonomy Strategies, USA)

PANEL 1: THE STRUCTURE OF SOCIAL CLASSIFICATION Exploring characteristics of social classification Xia Lin, Joan E. Beaudoin, Yen Bui, Kaushal Desai, and Tony Moore (Drexel University, USA)

Searching the long tail: Hidden structure in social tagging Emma Tonkin (UKOLN, UK)

Expertise classification: Collaborative classification vs. automatic extraction Toine Bogers, Willem Thoonen, and Antal van den Bosch (Tilburg University, The Netherlands)

PANEL 2: POSTER DISCUSSION
Folksonomies for image retrieval: How and why are personal images tagged?
Emma Angus (University of Wolverhampton, UK)

Social bookmarking in the enterprise
Michael D. Braly and Geoffrey B. Froh (University of Washington, USA)

Cognitive operations behind tagging for one's self and tagging for others Judd Butler (Florida State University, USA)

Ranking patterns: A Flickr tagging system pilot study Janet Capps (Florida State University, USA)

Folksonomies vs. bag-of-words: The evaluation and comparison of different types of document representations Anatoliy Gruzd (University of Illinois at Urbana-Champaign, USA)

Social classification and online job banks: Finding the right words to find the right job Kevin Harrington (Florida State University, USA)

Tag distribution analysis using the power law to evaluate social tagging systems: A case study in the Flickr database Hong Huang (Florida State University, USA)

@toread and cool: Tagging for time, task, and emotion Margaret E. I. Kipp (University of Western Ontario, Canada)

Ne'er-do-wells in Neverland: Mediation and conflict resolution in social classification environments Chris Landbeck (Florida State University, USA)

Exploratory study of classification tags in terms of cultural influences and implications for social classification Kyoungsik Na (Florida State University, USA)

Folksonomies or fauxsonomies: How social is social bookmarking?
Marina Pluzhenskaia (University of Illinois at Urbana-Champaign, USA)

Shared, persistent user search paths: Social navigation as social classification Robert J. Sandusky (University of Tennessee, Knoxville, USA)

The use of collaborative tagging in public library catalogues Louise Spiteri (Dalhousie University, Canada)

Using social bookmarks in an academic setting: PennTags Jennifer Erica Sweda (University of Pennsylvania, USA)

PANEL 3: SOCIAL CLASSIFICATION OF VISUAL RESOURCES Social classification in art museums: steve.museum Susan Chun (Metropolitan Museum of Art, New York, USA) and Jennifer Trant (Archives & Museum Informatics / University of Toronto, Canada)

Viewer tagging in art museums: Comparisons to concepts and vocabularies of art museum visitors Martha Kellogg Smith (University of Washington, USA)

User-defined classification on the online photo sharing site Flickr ... Or, How I learned to stop worrying and love the million typing monkeys Megan Winget (University of Texas at Austin, USA)

PANEL 4: CONCEPTUAL FRAMEWORKS FOR SOCIAL CLASSIFICATION An examination of authority in social classification systems Melanie Feinberg (University of Washington, USA)

A phenomenological framework for the relationship between the Semantic Web and user-centered tagging systems D. Grant Campbell (University of Western Ontario, Canada)

Social tagging and the next steps for indexing Joseph T. Tennis (University of British Columbia, Canada)

AIMS
The aims of this year's Classification Research Workshop are to provide a forum for researchers, practitioners, and users to share their knowledge, perspectives, and opinions on social classification (SC), and (in the form of the proceedings) to make a lasting and authoritative contribution to our understanding of the benefits that SC-based systems may provide. In the original call, papers on any aspect of the conceptualization and/or evaluation of social classification were invited for presentation at the workshop and publication in the open-access, peer-reviewed proceedings.

Social classification is a convenient, generic label that may be used to refer to any of a number of broadly related processes by which the resources in a collection are categorized by multiple people over an ongoing period, with the potential result that any given resource will come to be represented by a set of labels or descriptors that have been generated by different people. The specific processes in question include indexing, tagging, bookmarking, annotation, and description of kinds that may be characterized as collaborative, cooperative, distributed, dynamic, community-based, folksonomic, wikified, democratic, user-assigned, or user-generated. The mid-2000s have seen rapid growth in levels of interest in these kinds of technique for generating descriptions of resources for the purposes of discovery, access, and retrieval. Systems that provide automated support for social classification may be implemented at low cost, and are perceived to contribute to the democratization of classification by empowering people, who might otherwise remain strictly consumers of information, to become information producers.

Efforts to conduct serious evaluations of the comparative effectiveness of such systems have begun, but results are scattered and piecemeal. Compared with retrieval systems based on traditional methods -- manual or automatic -- of classifying resources, how effectively are users of SC-based systems able to find the resources that they want? What is the impact on retrieval effectiveness of systems designers' decisions to pay limited attention to traditionally important components such as vocabulary control, facet analysis, and systematic hierarchical arrangement? Current implementations of SC tend to shy away, for instance, from imposing the kind of vocabulary control on which classification schemes and thesauri are conventionally founded: proponents argue that social classifiers should be free, as far as possible, to supply precisely those class labels that they believe will be useful to searchers in the future, whether or not those labels have proven useful in the past. But do the advantages that are potentially to be gained from allowing classifiers free rein in the choice of labels outweigh those that may be obtainable by imposing some form of vocabulary and authority control, by offering browsing-based interfaces to hierarchically structured vocabularies, by establishing and complying with policies for the specificity and exhaustivity of sets of labels, and/or by other devices that are designed to improve classifier-- searcher consistency?

Other questions arise as a result of the reliance of SC-based systems on volunteer labor. Given the distributed nature of SC, for example, how can it be ensured that every resource attracts a critical mass of descriptors, rather than just the potentially-quirky choices of a small number of volunteers? Given the self-selection of classifiers, how can it be ensured that they are motivated to supply class labels that they would expect other searchers to use? In general, are reductions in the costs of classification (borne by information
producers) achieved only at the expense of increases in the costs of resource discovery (borne by consumers)?

PROGRAM COMMITTEE
Hanne Albrechtsen (Institute of Knowledge Sharing, Denmark)
Jack Andersen (Royal School of Library and Information Science, Denmark)
Clare Beghtol (University of Toronto, Canada)
Grant Campbell (University of Western Ontario, Canada)
Jonathan Furner (University of California, Los Angeles, USA) [co-chair]
Barbara Kwasnik (Syracuse University, USA)
Kathryn La Barre (University of Illinois at Urbana-Champaign, USA)
Joseph Tennis (University of British Columbia, Canada) [co-chair]
Douglas Tudhope (University of Glamorgan, UK)


Fees
Members $105, non-members $120 before Sept. 22
Members $120, non-members $145 after Sept. 22
This workshop does not qualify for a $75 discount