Tagging structure in a protein-protein interaction network, a co-authorship network and the (English) Wikipedia Protein s Math co- authors Wikipedia articles Network Nodes + Links Node tags Directed Acyclic Graph Gergely Palla, Illés J. Farka s , Péter Pollner, Imre Derényi, Tamás Vicsek Category tree FIFA World Cup FIFA World Cup Players Classification of co-authored papers Combinator ics Graph theory Biochemical functions Growth Cell growth Eötvös University and Hungarian Academy of Sciences (Budapest, Hungary) Interactions (“MIPS”) Co-authorships (“MathSciNet”) Hyperlinks in Wikipedia CFinder.org
Wikimania 2010-illesfarkas-v4
Aug 06, 2015
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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
DirectedAcyclicGraph
Gergely Palla, Illés J. Farkas, Péter 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
Eötvös 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 topicIn 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
AB
C D
E
F G
H
J
Meaningful removal of loops from the category hierarchyHow to achieve tree structure (DAG) with the lowest number of removals
Example (Oct.2007):
Category:Urdu Category:Hindustani
Finding all loops is easy.
But which of their links should be removed?
Goals: - Remove lowest possible number of links- Smallest “damage” to existing category hierarchy
subcategory
subcategory
CFinder.org
Meaningful removal of loops from the category hierarchyHow to achieve tree structure (DAG) with the lowest number of removals
Example (Oct.2007):
(1) Identify “loop subgraph”by iteratively removing nodes with 1 link
(2) Iteratively remove “least important” linksfrom the loop subgraph
(3) Add non-loop links again
AB
C D
E
F G
H
JCategory:Urdu Category:Hindustani
subcategory
subcategory
Finding all loops is easy.
But which of their links should be removed?
Goals: - Remove lowest possible number of links- Smallest “damage” to existing category hierarchy
Gergely Palla Illés Farkas Péter Pollner Imre Derényi Tamás Vicsek
http://CFinder.org -- with network data and free analysis software
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