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Tagging structure in a protein-protein interaction network, a co-authorship network and the (English) Wikipedia Proteins Math co-authors Wikipedia articles Network Nodes  + Links Node tags Directed Acyclic Graph Gergely Palla ,  Illés  J.  Farka s , P é ter Pollner , Imre Derényi, Tamás Vicsek Category tree FIFA World Cup FIFA World Cup Players Classification of co-authored papers Combinatorics Graph theory Biochemical functions Growth Cell growth E ötvös University and Hungarian Academy of Sciences (Budapest, Hungary) Interactions (“MIPS”) Co-authorships (“MathSciNet”) Hyperlinks in Wikipedia CFinder.org
G. Palla, I. J. Farkas, P. Pollner, I. Derényi, T. Vicsek  Fundamental statistical features and self-similar properties of tagged networks   New Journal of Physics   10 , 123026 (2008)  http://CFinder.org  --> Publications Full version:
There is no clearly separated group of “most popular tags” Transition between popular and less popular tags is  continuous Portion ( x ) of all nodes in the network Probability that a given tag and its descendants label a portion  x  of all nodes CFinder.org
There is no clear group of “most heavily tagged nodes” Transition between strongly and less strongly tagged nodes is  continuous Number of tags ( n ) on a node (protein, author, wiki article) of the network Probability that a node has  n  tags CFinder.org
On the large scale there is no “link saturation” within a topic In fact, link density within a large topic is  almost the same  as outside CFinder.org Number of links among these nodes Number of Wikipedia articles selected from those labeled with “Japan” and descendant terms Maximum possible Wikipedia average
CFinder.org A B C D E F G H J Meaningful removal of loops from the category hierarchy How to achieve tree structure (DAG) with the lowest number of removals Example (Oct.2007): ,[object Object],[object Object],[object Object],[object Object],[object Object],subcategory subcategory Category:Urdu  Category:Hindustani
CFinder.org Meaningful removal of loops from the category hierarchy How to achieve tree structure (DAG) with the lowest number of removals Example (Oct.2007): ,[object Object],[object Object],[object Object],[object Object],[object Object],A B C D E F G H J subcategory subcategory ,[object Object],[object Object],[object Object],[object Object],[object Object],Category:Urdu  Category:Hindustani
Gergely Palla  Illés Farka s  P é ter Pollner  Imre Derényi   Tamás Vicsek
http://CFinder.org -- with network data and free analysis software We thank for support from:

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Structure of tagging on Wikipedia pages and other networks -- Wikimania 2010 -- Gdansk

  • 1. Tagging structure in a protein-protein interaction network, a co-authorship network and the (English) Wikipedia Proteins Math co-authors Wikipedia articles Network Nodes + Links Node tags Directed Acyclic Graph Gergely Palla , Illés J. Farka s , P é ter Pollner , Imre Derényi, Tamás Vicsek Category tree FIFA World Cup FIFA World Cup Players Classification of co-authored papers Combinatorics Graph theory Biochemical functions Growth Cell growth E ötvös University and Hungarian Academy of Sciences (Budapest, Hungary) Interactions (“MIPS”) Co-authorships (“MathSciNet”) Hyperlinks in Wikipedia CFinder.org
  • 2. G. Palla, I. J. Farkas, P. Pollner, I. Derényi, T. Vicsek  Fundamental statistical features and self-similar properties of tagged networks   New Journal of Physics   10 , 123026 (2008)  http://CFinder.org --> Publications Full version:
  • 3. There is no clearly separated group of “most popular tags” Transition between popular and less popular tags is continuous Portion ( x ) of all nodes in the network Probability that a given tag and its descendants label a portion x of all nodes CFinder.org
  • 4. There is no clear group of “most heavily tagged nodes” Transition between strongly and less strongly tagged nodes is continuous Number of tags ( n ) on a node (protein, author, wiki article) of the network Probability that a node has n tags CFinder.org
  • 5. On the large scale there is no “link saturation” within a topic In fact, link density within a large topic is almost the same as outside CFinder.org Number of links among these nodes Number of Wikipedia articles selected from those labeled with “Japan” and descendant terms Maximum possible Wikipedia average
  • 6.
  • 7.
  • 8. Gergely Palla Illés Farka s P é ter Pollner Imre Derényi Tamás Vicsek
  • 9. http://CFinder.org -- with network data and free analysis software We thank for support from: