tagging, communities, vocabulary, evolution

ABSTRACT

A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.

REFERENCES

• 1: S. E. Asch. Effects of group pressure upon the modification and distortion of judgements. Groups, Leadership,and Men, pages 177--190, 1951.
• 2: Marko Balabanović , Yoav Shoham, Fab: content-based, collaborative recommendation, Communications of the ACM, v.40 n.3, p.66-72, March 1997 [doi>10.1145/245108.245124]
• 3: Vincent Bouthors , Olivier Dedieu, Pharos, a Collaborative Infrastructure for Web Knowledge Sharing, Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries, p.215-233, September 22-24, 1999
• 4: C. Cattuto, V. Loreto, and L. Pietronero. Semiotic dynamics in online social communities.In The European Physical Journal C (accepted). Springer-Verlag, 2006.
• 5: R. B. Cialdini. Influence Science and Practice. Allyn and Bacon, MA, USA, 2001.
• 6: Dan Cosley , Shyong K. Lam , Istvan Albert , Joseph A. Konstan , John Riedl, Is seeing believing?: how recommender system interfaces affect users' opinions, Proceedings of the SIGCHI conference on Human factors in computing systems, April 05-10, 2003, Ft. Lauderdale, Florida, USA [doi>10.1145/642611.642713]
• 7: D. Coye. A linguistic survey of college freshmen: Keeping up with standard American english. American Speech, 69(3): 260--284, 1994.
• 8: N. Glance, D. Arregui, and M. Dardenne. Knowledge pump: Supporting the flow and use of knowledge. In Information Technology for Knowledge Management. Springer-Verlag, 1998.
• 9: Scott A. Golder , Bernardo A. Huberman, Usage patterns of collaborative tagging systems, Journal of Information Science, v.32 n.2, p.198-208, April 2006 [doi>10.1177/0165551506062337]
• 10: M. Guy and E. Tonkin. Tidying up Tags? D-Lib Magazine, 12(1): 1082--9873, 2006.
• 11: T. Hammond, T. Hannay, B. Lund, and J. Scott. Social bookmarking tools: A general review. D-Lib Magazine, 11(4), April 2005.
• 12: G. MacGregor and E. McCulloch. Collaborative tagging as a knowledge organisation and resource discovery tool. Library View (accepted), 55(5), 2006.
• 13: David Millen , Jonathan Feinberg , Bernard Kerr, Social bookmarking in the enterprise, Queue, v.3 n.9, November 2005 [doi>10.1145/1105664.1105676]
• 14: Alan J. Munro , D. J. Sanger , D. R. Benyon, Personal and Social Navigation of Information Space, Springer-Verlag, London, 1999
• 15: J. A. Ouellette and W. Wood. Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Review, 127: 54--74, 1998.
• 16: Luis von Ahn , Laura Dabbish, Labeling images with a computer game, Proceedings of the SIGCHI conference on Human factors in computing systems, p.319-326, April 24-29, 2004, Vienna, Austria [doi>10.1145/985692.985733]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces
          Subjects: Collaborative computing

Additional Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human information processing
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)

General Terms:
Design, Experimentation, Human Factors

Keywords:
communities, evolution, social book-marking, tagging, vocabulary