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Stop thinking, start tagging: Tag Semantics arise from Collaborative Verbosity

Stop thinking, start tagging: Tag Semantics arise from Collaborative Verbosity. Christian Körner 1 , Dominik Benz 2 , Andreas Hotho 3 , Markus Strohmaier 1 , Gerd Stumme 2. 1 Knowledge Management Institute and Know Center, Graz University of Technology, Austria.

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Stop thinking, start tagging: Tag Semantics arise from Collaborative Verbosity

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  1. Stop thinking, start tagging:Tag Semantics arise from Collaborative Verbosity Christian Körner1, Dominik Benz2, Andreas Hotho3, Markus Strohmaier1, Gerd Stumme2 1Knowledge Management Institute and Know Center, Graz University of Technology, Austria 2Knowledge and Data Engineering Group (KDE), University of Kassel, Germany 3Data Mining and Information Retrieval Group University of Würzburg, Germany

  2. Where do Semantics come from? • Semantically annotated content is the „fuel“ of the next generation World Wide Web – but where is the petrol station? • Expert-built  expensive • Evidence for emergent semantics in Web2.0 data  Built by the crowd!  Which factors influence emergence of semantics?  Do certain users contribute more than others? Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  3. The Story Pragmatics of tagging Emergent Tag Semantics Semantic Implications of Tagging Pragmatics Conclusions Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  4. Emergent Tag Semantics • tagging is a simple and intuitive way to organize all kinds of resources • uncontrolled vocabulary, tags are „just strings“ • formal model: folksonomyF = (U, T, R, Y) • UsersU, Tags T, ResourcesR • Tag assignmentsY  (UTR) • evidence of emergent semantics • Tag similarity measures canidentify e.g. synonym tags (web2.0, web_two) Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  5. Tag Similarity Measures: Tag Context Similarity • Tag Context Similarity is a scalable and precise tag similarity measure [Cattuto2008,Markines2009]: • Describe each tag as a context vector • Each dimension of the vector space correspond to another tag; entry denotes co-occurrence count • Compute similar tags by cosine similarity … JAVA design software blog web programming  Will be used as indicator of emergent semantics! Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  6. WordNet Hierarchy Mapping = synset Average JCN(t,tsim) over all tags t: „Quality of semantics“ = tag Assessing the Quality of Tag Semantics Folksonomy Tags JCN(t,tsim) = 3.68 TagCont(t,tsim) = 0.74 Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  7. The Story Pragmatics of tagging Tag Similarity measures can capture emergent tag semantics Semantic Implications of Tagging Pragmatics Conclusions Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  8. bev donuts duff alc nalc bart Duff-beer wine beer marge beer barty Tagging motivation • Evidence of different ways HOW users tag (Tagging Pragmatics) • Broad distinction by tagging motivation [Strohmaier2009]: • „Describers“… • tag „verbously“ with freely chosen words • vocabulary not necessarily consistent (synomyms, spelling variants, …) • goal: describe content, ease retrieval • „Categorizers“… • use a small controlled tag vocabulary • goal: „ontology-like“ categorization by tags, for later browsing • tags a replacement for folders Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  9. high low Tagging Pragmatics: Measures • How to disinguish between two types of taggers? • Intuition: Describers use open set of many tags, Categorizers use small set of controlled tags: • Vocabulary size: • Tag / Resource ratio: • Average # tags per post: Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  10. Tagging Pragmatics: Measures • Next Intuition: Describers don‘t care about „abandoned“ tags, Categorizers do • Orphan ratio: • R(t): set of resources tagged by user u with tag t high low Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  11. Tagging pragmatics: Limitations of measures • Real users: no „perfect“ Categorizers / Describers, but „mixed“ behaviour • Possibly influenced by user interfaces / recommenders • Measures are correlated • But: independent of semantics; measures capture usage patterns Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  12. The Story Measures of tagging pragmatics differentiate users by tagging motivation Tag Similarity measures can capture emergent tag semantics Semantic Implications of Tagging Pragmatics Conclusions Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  13. = user Subset of 30% categorizers Influence of Tagging Pragmatics on Emergent Semantics • Idea: Can we learn the same (or even better) semantics from the folksonomy induced by a subset of describers / categorizers? Complete folksonomy Extreme Categorizers Extreme Describers Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  14. TagCont(t,tsim)= … JCN(t,tsim)= … CF5 DF20 Experimental setup • Apply pragmatic measures vocab, trr, tpp, orphan to each user • Systematically create „sub-folksonomies“ CFi / DFi by subsequently adding i % of Categorizers / Describers (i = 1,2,…,25,30,…,100) • Compute similar tags based on each subset (TagContext Sim.) • Assess (semantic) quality of similar tags by avg. JCN distance Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  15. Dataset • From Social Bookmarking Site Delicious in 2006  ORIGINAL • Two filtering steps (to make measures more meaningful): • Restrict to top 10.000 tags FULL • Keep only users with > 100 resources MIN100RES Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  16. Almost all sub-folksonomies are better than random-picked ones 40% of describers according to trr outperform complete data! Optimal performance for 70% describers (trr) Results – adding Describers (DFi) better semantics more describers Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  17. Almost all sub-folksonomies are worse than random-picked ones Global optimum for 90% categorizers (tpp)  removing 10% most extreme describers!(Spammers?) Results – adding Categorizers (CFi) better semantics more categorizers Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  18. Measures of tagging pragmatics differentiate users by tagging motivation The Story Tag Similarity measures can capture emergent tag semantics Sub-folksonomies introduced by measures of pragmatics show different semantic qualities Conclusions Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  19. Summary & Conclusions • Introduction of measures of users‘ tagging motivation (Categorizers vs. Describers) • Evidence for causal link between tagging pragmatics (HOW people use tags) and tag semantics (WHAT tags mean) • „Mass matters“ for „wisdom of the crowd“, but composition of crowd makes a difference („Verbosity“ of describers in general better, but with a limitation) • Relevant for tag recommendation and ontology learning algorithms Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  20. Guess who‘s a Categorizer from the authors  Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  21. Measures of tagging pragmatics differentiate users by tagging motivation Thanks for the attention! Questions? Be verbous  christian.koerner@tugraz.atbenz@cs.uni-kassel.de Tag Similarity measures can capture emergent tag semantics Sub-folksonomies introduced by measures of pragmatics show different semantic qualities Evidende of causal link between pragmatics and semantics of tagging! Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

  22. References • [Cattuto2008] Ciro Cattuto, Dominik Benz, Andreas Hotho, Gerd Stumme: Semantic Grounding of Tag Relatedness in Social Bookmarking Systems. In: Proc. 7th Intl. Semantic Web Conference (2008), p. 615-631 • [Markines2009] Benjamin Markines, Ciro Cattuto, Filippo Menczer, Dominik Benz, Andreas Hotho, Gerd Stumme: Evaluating Similarity Measures for Emergent Semantics of Social Tagging. In: Proc. 18th Intl. World Wide Web Conference (2009), p.641-641 • [Strohmaier2009] Markus Strohmaier, Christian Körner, Roman Kern: Why do users tag? Detecting users‘ motivation for tagging in social tagging systems. Technical Report, Knowledge Management Institute – Graz University of Technology (2009) Körner, Benz et al.: Tag Semantics arise from Collaborative Verbosity @ WWW2010

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