Disentangling categorical relationships through a graph of co-occurrences

Juan Martinez-Romo, Lourdes Araujo, Javier Borge-Holthoefer, Alex Arenas, José A. Capitán, José A. Cuesta

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16 Citations (Scopus)

Abstract

The mesoscopic structure of complex networks has proven a powerful level of description to understand the linchpins of the system represented by the network. Nevertheless, the mapping of a series of relationships between elements, in terms of a graph, is sometimes not straightforward. Given that all the information we would extract using complex network tools depend on this initial graph, it is mandatory to preprocess the data to build it on in the most accurate manner. Here we propose a procedure to build a network, attending only to statistically significant relations between constituents. We use a paradigmatic example of word associations to show the development of our approach. Analyzing the modular structure of the obtained network we are able to disentangle categorical relations, disambiguating words with success that is comparable to the best algorithms designed to the same end.

Original languageEnglish
Article number046108
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume84
Issue number4
DOIs
Publication statusPublished - 19 Oct 2011

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ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

Cite this

Martinez-Romo, J., Araujo, L., Borge-Holthoefer, J., Arenas, A., Capitán, J. A., & Cuesta, J. A. (2011). Disentangling categorical relationships through a graph of co-occurrences. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 84(4), [046108]. https://doi.org/10.1103/PhysRevE.84.046108