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Workshop on FOLKSONOMIES   Singapore, February 9, 2009
We are very proud to hold a workshop in the „informational city“ of Singapore.
Wolfgang G. Stock Isabella Peters Researcher, Dept. for Information Science, Heinrich-Heine-University Düsseldorf, Germany Lectures on Web 2.0 Services and Information Retrieval  Main research area: Folksonomies in Knowledge Representation and Information Retrieval Professor, Head of Dept.  for Information Science,  Heinrich-Heine-University  Düsseldorf, Germany Lectures on Information Retrieval, Knowledge Representation, Informetrics and Information Market Main research areas: Folksonomies, Emotional Information Retrieval and Informetrics of LIS Journals
Social Network on our Workshop ,[object Object],[object Object],http://taggingworkshop.ning.com/
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lesson 1 Folksonomies – Indexing without Rules
Indexing without Rules ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Indexing
Prosumer ,[object Object],[object Object],[object Object],Producer Consumer Prosumer
Tri-partite System ,[object Object],[object Object],[object Object]
Cognitive Indexing Processes Source:  Sinha (2005)
Library 2.0
 
 
Network Economy: Positive Feedback Loop Time Number of active (tagging) users Critical Mass New users come along. Value of the network increase. Number of users of  the network increase. „ success breeds success“ only  one  standard (in a technological area)
Time red: Competitor yellow: Your Library 2.0 Service „ Combat Area“ „ Take off“ Positive Feedback „ Saturation“ „ Entry“ Number of active (tagging) users Critical Mass
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],How to Become a Standard (Part 1)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],How to Become a Standard (Part 2)
Lesson 2 Folksonomies in Information Services and Library Catalogues
Narrow Folksonomies ,[object Object],[object Object],[object Object],Tags
Extended Narrow Folksonomies ,[object Object],[object Object],[object Object],Source:  Vander Wal (2005)   Tags Add Tags Option
Broad Folksonomies ,[object Object],[object Object],[object Object],Source:  Vander Wal (2005)   Tags
Tagging of OPACs ,[object Object],[object Object],[object Object]
Tagging of OPACS: Within Library’s Website: PennTags http://tags.library.upenn.edu/
Tagging of OPACS: Within Library’s Website: Ann Arbor District Library http://www.aadl.org/catalog
Tagging of OPACS: Within Library’s Website: University Library Hildesheim http://www.uni-hildesheim.de/mybib/all_tags
Tagging of OPACS: Within Library’s Website ,[object Object],[object Object],[object Object],[object Object],[object Object]
Tagging of OPACS: Within Library’s Website ,[object Object],[object Object],[object Object],[object Object]
Tagging of Resources Outside the Library‘s Firewall: HEIDI http://katalog.ub.uni-heidelberg.de/cgi-bin/search.cgi
Tagging of Resources Outside the Library‘s Firewall: LibraryThing http://www.librarything.com/search
Tagging of Resources Outside the Library‘s Firewall: BibSonomy http://www.bibsonomy.org/
Tagging of Resources Outside the Library‘s Firewall ,[object Object],[object Object],[object Object],[object Object],[object Object]
Tagging of Resources Outside the Library‘s Firewall ,[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC – Thoughts which have to be made in advance ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC: Benefits ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC: Benefits ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC: Benefits ,[object Object],[object Object],[object Object],[object Object],[object Object]
Social OPAC: Benefits ,[object Object],[object Object],[object Object],[object Object],[object Object]
Short Break
Lesson 3 Folksonomies and Knowledge Representation
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Collective Intelligence
Power Law Tag Distribution Source : http:// del.icio.us f (x)= C / x a Users Tags 80/20-Rule Long Tail Power Tags
Inverse-logistic Tag Distribution Source : http:// del.icio.us Users Tags f (x)= e -C‘(x-1) b Long Trunk Long Tail Power Tags
Document-specific Tag Distributions distributions of the top 10 tags in a broad folksonomy (sample: Delicious) N = 650 bookmarks (minimum of 100 different taging users) Source : Reher (2008); unpublished
[object Object],[object Object],Power Tags Power Tags Power Tags
Tagging Behaviour ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Source:  Sen et al. (2006)   Source:  Rader & Wash (2008 )
Sentiment Tags ,[object Object],[object Object],[object Object],Source:  Yanbe et al. (2007); service: Hatena Bookmarks
Documents which Provoke Emotions Tagging using scroll-bars Source:  Schmidt and Stock (2009)
Tag Types
Discrimination Power of Tags low discrimination very low discrimination rare “ Long tail” strong discrimination low discrimination frequent “ Power tags” rare frequent Tags in Concrete Document Tags in Folksonomy
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Benefits of Indexing with Folksonomies
Disadvantages of Indexing with Folksonomies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lesson 4 Folksonomies and Information Retrieval
[object Object],[object Object],Knowledge Representation  and  Information Retrieval Knowledge Representation Information Retrieval Knowledge Representation without Information Retrieval is empty. Information Retrieval without Knowledge Representation is blind. Feedback Loop
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Information Linguistics
Relevance Ranking: State of the Art ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Relevance Ranking of Tagged Documents Source:  Peters and Stock (2007)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Retrieval Status Value – Factor 1: Tags tag evaluation
[object Object],[object Object],[object Object],[object Object],Retrieval Status Value – Factor 2:  Collaboration
[object Object],[object Object],[object Object],Retrieval Status Value – Factor 3:  Prosumer
Short Break
Lesson 5 Tag Gardening for Folksonomy Enrichment and Maintenance
The Folksonomy Tag Garden
Goal of Tag Gardening: Emergent Semantics
[object Object],[object Object],[object Object],[object Object],[object Object],Weeding
[object Object],[object Object],[object Object],[object Object],Seeding
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Landscape Architecture
[object Object],[object Object],[object Object],Fertilizing
Emergent Semantics ,[object Object],[object Object],[object Object],Synonyms Is_a
(geographical) meronymy synonymy hyponymy Hidden Paradigmatic Relations Source : http:// www.flickr.com
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Hidden Paradigmatic Relations.  Flickr Landscape Photos Source : own research project
From Tag Gardening to Collaborative  KOS Development ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Maintenance of KOS and Folksonomy Source : Christiaens (2006) Folksonomy KOS Tag Gardening new terms – new relations
From Tag Clouds to Tag Clusters ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Source:  Knautz (2008)
Lesson 6 Find „More like me!“  The Social Function of a Folksonomy
Users – Tags - Documents thematically linked shared users thematically linked shared documents
Shared Documents & Thematically  Linked Users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],thematically linked shared documents
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],More like me! Or: More like This User!
More like me! Or: More like This User! single linkage clustering (fictitious example) Sim(tag) = 0.21 Sim(doc) = 0.25 Sim(tag) = 0.65 Sim(doc) = 0.55 Sim(tag) = 0.33 Sim(doc) = 0.29 Sim(tag) = 0.17 Sim(doc) = 0.23 Sim(tag) = 0.08 Sim(doc) = 0.11 Sim(tag) = 0.15 Sim(doc) = 0.17 Sim(tag) = 0.45 Sim(doc) = 0.36
The Social Function of a Folksonomy ,[object Object],[object Object],[object Object],[object Object]
Final Discussion Folksonomies in Library Catalogues – Lessons Learned
Lessons Learned ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned ,[object Object],[object Object],[object Object],[object Object]
We would like to thank you very much for attending this Workshop. Greetings from Düsseldorf, Germany!

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Folksonomies: In General and in Libraries

  • 1. Workshop on FOLKSONOMIES Singapore, February 9, 2009
  • 2. We are very proud to hold a workshop in the „informational city“ of Singapore.
  • 3. Wolfgang G. Stock Isabella Peters Researcher, Dept. for Information Science, Heinrich-Heine-University Düsseldorf, Germany Lectures on Web 2.0 Services and Information Retrieval Main research area: Folksonomies in Knowledge Representation and Information Retrieval Professor, Head of Dept. for Information Science, Heinrich-Heine-University Düsseldorf, Germany Lectures on Information Retrieval, Knowledge Representation, Informetrics and Information Market Main research areas: Folksonomies, Emotional Information Retrieval and Informetrics of LIS Journals
  • 4.
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  • 6. Lesson 1 Folksonomies – Indexing without Rules
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  • 11. Cognitive Indexing Processes Source: Sinha (2005)
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  • 15. Network Economy: Positive Feedback Loop Time Number of active (tagging) users Critical Mass New users come along. Value of the network increase. Number of users of the network increase. „ success breeds success“ only one standard (in a technological area)
  • 16. Time red: Competitor yellow: Your Library 2.0 Service „ Combat Area“ „ Take off“ Positive Feedback „ Saturation“ „ Entry“ Number of active (tagging) users Critical Mass
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  • 19. Lesson 2 Folksonomies in Information Services and Library Catalogues
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  • 24. Tagging of OPACS: Within Library’s Website: PennTags http://tags.library.upenn.edu/
  • 25. Tagging of OPACS: Within Library’s Website: Ann Arbor District Library http://www.aadl.org/catalog
  • 26. Tagging of OPACS: Within Library’s Website: University Library Hildesheim http://www.uni-hildesheim.de/mybib/all_tags
  • 27.
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  • 29. Tagging of Resources Outside the Library‘s Firewall: HEIDI http://katalog.ub.uni-heidelberg.de/cgi-bin/search.cgi
  • 30. Tagging of Resources Outside the Library‘s Firewall: LibraryThing http://www.librarything.com/search
  • 31. Tagging of Resources Outside the Library‘s Firewall: BibSonomy http://www.bibsonomy.org/
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  • 47. Lesson 3 Folksonomies and Knowledge Representation
  • 48.
  • 49. Power Law Tag Distribution Source : http:// del.icio.us f (x)= C / x a Users Tags 80/20-Rule Long Tail Power Tags
  • 50. Inverse-logistic Tag Distribution Source : http:// del.icio.us Users Tags f (x)= e -C‘(x-1) b Long Trunk Long Tail Power Tags
  • 51. Document-specific Tag Distributions distributions of the top 10 tags in a broad folksonomy (sample: Delicious) N = 650 bookmarks (minimum of 100 different taging users) Source : Reher (2008); unpublished
  • 52.
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  • 55. Documents which Provoke Emotions Tagging using scroll-bars Source: Schmidt and Stock (2009)
  • 57. Discrimination Power of Tags low discrimination very low discrimination rare “ Long tail” strong discrimination low discrimination frequent “ Power tags” rare frequent Tags in Concrete Document Tags in Folksonomy
  • 58.
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  • 60. Lesson 4 Folksonomies and Information Retrieval
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  • 64. Relevance Ranking of Tagged Documents Source: Peters and Stock (2007)
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  • 69. Lesson 5 Tag Gardening for Folksonomy Enrichment and Maintenance
  • 71. Goal of Tag Gardening: Emergent Semantics
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  • 77. (geographical) meronymy synonymy hyponymy Hidden Paradigmatic Relations Source : http:// www.flickr.com
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  • 80. Maintenance of KOS and Folksonomy Source : Christiaens (2006) Folksonomy KOS Tag Gardening new terms – new relations
  • 81.
  • 82. Lesson 6 Find „More like me!“ The Social Function of a Folksonomy
  • 83. Users – Tags - Documents thematically linked shared users thematically linked shared documents
  • 84.
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  • 86. More like me! Or: More like This User! single linkage clustering (fictitious example) Sim(tag) = 0.21 Sim(doc) = 0.25 Sim(tag) = 0.65 Sim(doc) = 0.55 Sim(tag) = 0.33 Sim(doc) = 0.29 Sim(tag) = 0.17 Sim(doc) = 0.23 Sim(tag) = 0.08 Sim(doc) = 0.11 Sim(tag) = 0.15 Sim(doc) = 0.17 Sim(tag) = 0.45 Sim(doc) = 0.36
  • 87.
  • 88. Final Discussion Folksonomies in Library Catalogues – Lessons Learned
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  • 95. We would like to thank you very much for attending this Workshop. Greetings from Düsseldorf, Germany!

Notas do Editor

  1. Zu Punkt 3): In some cases, taggers are allowed to view the full content of a given resource, and then to assign, directly to that resource, tags that describe it; in others, taggers are allowed merely to view the record describing a given resource, and then to enhance that record by adding to it tags that further describe the resource.
  2. Zu Punkt 3): For instance, are tags searched when users do “keyword” searches of the OPAC? Is it possible to search or browse tags from within the OPAC?
  3. Zu Punkt 2): (i) by enhancing the quality of existing records, and/or (ii) by allowing users to discover resources in a new way, viz. by taking account of the recommendations of other users like themselves; Zu Punkt 3): by offering users the opportunity to bookmark resources that they like and that they predict they will wish to access again;
  4. Zu Punkt 2): (i) by enhancing the quality of existing records, and/or (ii) by recommending resources that are determined to be of potential interest to others