towards understanding the motivation behind tagging

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  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 20111

    Towards Understanding the Motivation Behind Tagging

    Christian Krner

    Knowledge Management InstituteGraz University of Technology

    presentation

    @Mendeley

    PhDWorkInPro

    gress

    4Feb2010taggingmotivationtodoimportant

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Outline of Todays Talk

    Introduction Motivation Research Questions Related Work What happened so far? Two Different Types of Tagging Motivation Expected Contribution Outlook

    2

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Introduction / 1

    Tagging is an easy and intuitive way to annotate resources

    A lot of current web platforms enable the tagging of resources

    Tags: are simple strings add additional metadata to a resource support re-finding of resources enable the browsing of a users resource collection mostly do not follow a controlled vocabulary

    How and which tags are applied to a resource depends on the user!

    3

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Introduction / 2

    Examples of Social Tagging Systems

    4

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Introduction / 3

    Resulting structure of social tagging systems consists of: Users Tags Resources

    Folksonomy (all users of a system)Personomy (one user of a system)

    5

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Motivation

    Getting a closer look at the motivation users of tagging systems have

    Inferring which users/tags are good for certain tasks: searching in these systems ontology learning classification

    Improve tag recommendation engines

    Simulation of users and folksonomies

    6

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Research Questions

    Is it possible to measure tagging motivation automatically?

    How do different motivations influence and transform resulting folksonomies?

    Based on these findings: Can we improve existing mechanisms (such as tag

    recommendation)? Is it possible to simulate whole folksonomies?

    7

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Related Work (excerpt)[Golder2006] - studies folksonomies as a whole, shows stable

    patterns. Present a dynamic model of collaborative tagging.

    [Nov2009] - different motivations in an online photo sharing system: enjoyment, commitment, self development, reputation

    [Heckner2009] - studied resource sharing vs. personal information management in social tagging systems and propose model of information behavior in social tagging systems

    But all previous work relies on expert judgement!

    8

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    What happened so far?

    Identification of two types of tagging motivation (two others are in the pipeline as well)

    Developed measures to detect the behavior

    Showed how tagging motivation can influence the resulting tags of a folksonomy and ontology learning[Krner2010a]

    Evaluated measures to identify the best for the differentiation [Krner2010b]

    9

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Two Different Extreme Types of Tagging Motivation (so far)

    Categorizers

    10

    Describers

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Categorizers - Using Tags for Categorization

    Main focus: using tags for mimicking a taxonomy created by their personal preferences

    they utilize tags so that their resources can be browsed more easily later

    avoid synonyms use limited tagging vocabulary use subjective tags

    11

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Describers - Using Tags to Describe Resources

    Main focus: describing resources as detailed as possible

    support search with their usage of tags tagging vocabulary can contain synonyms have an open tagging vocabulary use objective vocabulary

    12

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    (Current) Detection Measures

    Agnostic to semantics of used language

    Evaluate user behavior of single user (as opposed to the complete folksonomy) no comparison to complete folksonomy necessary

    Inspect the usage of tags NOT their semantics: How often are tags used? How good does a user encode her resources with tags? How many tags are used to annotate a single resource etc.

    13

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Results

    An early stage of this work was presented at the ACM SRC Hypertext 2009 conference and won the 1st prize

    Cooperation with KDE Kassel which resulted in a publication at the WWW2010

    One of the results of this work is that tagging pragmatics has impact on the semantic structure within a folksonomy

    In essence: Describers are better for the semantics within a tagging system

    Evaluation which measures perform best to differ types Hypertext 2010

    14

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Some additional papersExamining which measures are better for measuring the

    generality of tags Evaluate different folksonomy based measures with the help four different

    grounding sets

    Currently under review at ESWC

    Identifying the impact of user behavior on automated classification

    Automatically categorizing books into LCC and Dewey Classification Scheme Categorizers are also good for something! Although they use not that many words which are found in the descriptive

    data, they perform better with regard to classification.

    Currently under review at HT2011

    15

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Expected Contribution

    Getting a closer look at the reasons why users tag

    Improve recommendation engines

    Enhancing search

    Enhancement of automated ontology learning

    Possible identification of spammers

    16

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Possible Outlook

    Examine how tag recommendation can profit from knowledge of user motivation

    Investigate additional types of tagging motivation

    Using social network analysis for further investigation

    Using identified types of tagging motivation to build simulators

    Start writing the thesis

    17

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Conclusion

    Insight into my research on motivation behind tagging

    Quick introduction about tagging Motivation & Research Questions Related Work

    Categorizer VS. Describers Work which was done so far Expected Contribution & Outlook

    18

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    Thank You For Your Attention

    Please feel free to ask questions!

    19

    Friday, February 11, 2011

  • TU Graz Knowledge Management Institute

    Christian Krner Graz, February 4th, 2011

    References[Ames2007] Ames, M. & Naaman, M. (2007), Why we tag: motivations for annotation in mobile

    and online media, in CHI 07: Proceedings of the SIGCHI conference on Human factors in computing systems ACM, New York, NY, USA, pp.971--980

    [Golder2006] Golder S. & Huberman B.; Usage Patterns of Collaborative Tagging Systems; Journal of Information Science; 32(2):198, 2006

    [Heckner2009] Heckner, M; Heilemann, M. & Wolff, C. (2009) Personal Information Management vs. Resource Sharing: Towards a Model of Information Behavior in Social Tagging Systems, in Intl AAAI Conference on Weblogs and Social Media (ICWSM).

    [Krner2010a] Krner, C.; Benz, D.; Strohmaier, M.; Hotho, A. & Stumme, G. (2010), Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity, in 'Proceedings of the 19th International World Wide Web Conference (WWW 2010)', ACM, Raleigh, NC, USA.

    [Krner2010b] Krner, C.; Kern, R.; Grahsl, H. P. & Strohmaier, M. (2010), Of Categorizers and Describers: An Evaluation of Quantitative Measures for Tagging Motivation, in '21st ACM SIGWEB Conference on Hypertext and Hypermedia (HT 2010)', ACM, Toronto, Canada.

    [Nov2009] Nov, O.; Naaman, M. & Ye, C. (2010), 'Analysis of participation in an online photo-sharing community: A multidimensional perspective.', JASIST 61(3), 555-566.

    20

    Frida