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The European Physical Journal Special Topics

, Volume 225, Issue 10, pp 2025–2032 | Cite as

Comparing the hierarchy of author given tags and repository given tags in a large document archive

  • Gergely TibélyEmail author
  • Péter Pollner
  • Gergely Palla
Regular Article Computational Social Science
Part of the following topical collections:
  1. Complex, Inter-networked Economic and Social Systems

Abstract

Folksonomies – large databases arising from collaborative tagging of items by independent users - are becoming an increasingly important way of categorizing information. In these systems users can tag items with free words, resulting in a tripartite item-tag-user network. Although there are no prescribed relations between tags, the way users think about the different categories presumably has some built in hierarchy, in which more special concepts are descendants of some more general categories. Several applications would benefit from the knowledge of this hierarchy. Here we apply a recent method to check the differences and similarities of hierarchies resulting from tags given by independent individuals and from tags given by a centrally managed repository system. The results from our method showed substantial differences between the lower part of the hierarchies, and in contrast, a relatively high similarity at the top of the hierarchies.

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References

  1. 1.
    P. Mika, Ontologies are us: A unified model of social networks and semantics, Int. Semantic Web Conf., 3729522 (2005)Google Scholar
  2. 2.
    P. Spyns, A.D. Moor, J. Vandenbussche, R. Meersman, From Folksologies to Ontologies: How the Twain Meet, Proc. OTM Conf., 1738 (2006)Google Scholar
  3. 3.
    J. Voss, Tagging, folksonomy & Co – renaissance of manual indexing? [arXiv:cs/0701072v2] (2007)
  4. 4.
    C. Cattuto, V. Loreto, L. Pietronero, Proc. Natl. Acad. Sci. USA 104, 1461 (2007)ADSCrossRefGoogle Scholar
  5. 5.
    R. Lambiotte, M. Ausloos, Lect. Notes in Computer Sci. 3993, 1114 (2006)CrossRefGoogle Scholar
  6. 6.
    C. Cattuto, A. Barrat, A. Baldassarri, G. Schehr, V. Loreto, Proc. Natl. Acad. Sci. USA 106, 10511 (2009)ADSCrossRefGoogle Scholar
  7. 7.
    A. Plangprasopchok, K. Lerman, Constructing folksonomies from user-specified relations on flickr, Proc. of the World Wide Web conference (2009), p. 781Google Scholar
  8. 8.
    A. Plangprasopchok, K. Lerman, L. Getoor, A probabilistic approach for learning folksonomies from structured data, Fourth ACM Int. Conf. on Web Search and Data Mining (WSDM) (yr2011), p. 555Google Scholar
  9. 9.
    C.V. Damme, M. Hepp, K. Siorpaes, Social Networks 2, 57 (2007)Google Scholar
  10. 10.
    P. Schmitz, Inducing ontology from flickr tags, Proc. of Collaborative Web Tagging Workshop at the 15th Int. Conf. on World Wide Web (WWW) (2006)Google Scholar
  11. 11.
    P. Heymann, H. Garcia-Molina, Collaborative creation of communal hierarchical taxonomies in social tagging systems. Technical report, Stanford InfoLab (2006) URL http://ilpubs.stanford.edu:8090/775/
  12. 12.
    G. Tibély, P. Pollner, T. Vicsek, G. Palla, PLoS ONE 8, e84133 (2013)ADSCrossRefGoogle Scholar
  13. 13.
    H.W. Ma, J. Buer, A.P. Zeng, BMC Bioinformatics 5, 199 (2004)CrossRefGoogle Scholar
  14. 14.
    C. Goessmann, C. Hemelrijk, R. Huber, Behav. Ecol. Sociobiol. 48, 418 (2000)CrossRefGoogle Scholar
  15. 15.
    M. Nagy, Z. Ãkos, D. Biro, T. Vicsek, Nature 464, 890 (2010)ADSCrossRefGoogle Scholar
  16. 16.
    H. Fushing, M.P. McAssey, B. Beisner, B. McCowan, PLoS ONE 6, e17817 (2011)ADSCrossRefGoogle Scholar
  17. 17.
    M. Kaiser, C.C. Hilgetag, R. Kötter, Front. Neuroinform. 4, 112 (2010)CrossRefGoogle Scholar
  18. 18.
    D. Pumain, Hierarchy in Natural and Social Sciences. Methodos Series 3 (Springer Netherlands, Dodrecht, The Netherlands, 2006)Google Scholar
  19. 19.
    R. Guimerà, L. Danon, A. Díaz-Guilera, F. Giralt, A. Arenas, Phys. Rev. E. 68, 065103 (2003)ADSCrossRefGoogle Scholar
  20. 20.
    P. Pollner, G. Palla, T. Vicsek, Europhys. Lett. 73, 478 (2006)ADSMathSciNetCrossRefGoogle Scholar
  21. 21.
    S. Valverde, R.V. Solé, Phys. Rev. E. 76, 046118 (2007)ADSCrossRefGoogle Scholar
  22. 22.
    P.R. Krugman, J. Jpn Int. Econ. 10, 399 (1996)CrossRefGoogle Scholar
  23. 23.
    M. Batty, P. Longley, Fractal Cities: A Geometry of Form and Function (Academic, San Diego, 1994)Google Scholar
  24. 24.
    H. Hirata, R. Ulanowicz, J. Theor. Biol. 116, 321 (1985)MathSciNetCrossRefGoogle Scholar
  25. 25.
    J. Wickens, R. Ulanowicz, J. Soc. Biol. Struct. 11, 369 (1988)CrossRefGoogle Scholar
  26. 26.
    N. Eldredge, Unfinished Synthesis: Biological Hierarchies and Modern Evolutionary Thought (Oxford University Press, New York, 1985)Google Scholar
  27. 27.
    D.W. McShea, Paleobiology 27, 405 (2001)CrossRefGoogle Scholar
  28. 28.
    A. Trusina, S. Maslov, P. Minnhagen, K. Sneppen, Phys. Rev. Lett. 92, 178702 (2004)ADSCrossRefGoogle Scholar
  29. 29.
    B. Corominas-Murtra, C. Rodríguez-Caso, J. Goñi, R. Solé, Chaos 21, 016108 (2011)ADSMathSciNetCrossRefGoogle Scholar
  30. 30.
    E. Mones, L. Vicsek, T. Vicsek, PLoS ONE 7, e33799 (2012)ADSCrossRefGoogle Scholar
  31. 31.
    B. Corominas-Murtra, J. Goñi, R.V. Solé, C. Rodréguez-Caso, Proc. Natl. Acad. Sci. USA 110, 13316 (2013)ADSMathSciNetCrossRefGoogle Scholar
  32. 32.
    A. Clauset, C. Moore, M.E.J. Newman, Nature 453, 98 (2008)ADSCrossRefGoogle Scholar
  33. 33.
    E. Ravasz, A.L. Somera, D.A. Mongru, Z.N. Oltvai, A.-L. Barabási, Science 297, 1551 (2002)ADSCrossRefGoogle Scholar
  34. 34.
    Isi web of knowledge. http://scientific.thomson.com/isi/ (Date of access: 01/01/2012)
  35. 35.
    G. Palla, G. Tibély, E. Mones, P. Pollner, T. Vicsek, [arXiv:1506.05661] To appear in Palgrave Communications (2015)
  36. 36.

Copyright information

© EDP Sciences and Springer 2016

Authors and Affiliations

  • Gergely Tibély
    • 1
    Email author
  • Péter Pollner
    • 2
  • Gergely Palla
    • 2
  1. 1.Dept. of Biological Physics, Eötvös UniversityBudapestHungary
  2. 2.MTA-ELTE Statistical and Biological Physics Research Group, Hungarian Academy of SciencesBudapestHungary

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