Extracting directed information flow networks: an application to genetics and semantics
Data Analysis, Statistics and Probability
2011-02-15 v2 Social and Information Networks
Physics and Society
Abstract
We introduce a general method to infer the directional information flow between populations whose elements are described by n-dimensional vectors of symbolic attributes. The method is based on the Jensen-Shannon divergence and on the Shannon entropy and has a wide range of application. We show here the results of two applications: first extracting the network of genetic flow between the meadows of the seagrass Poseidonia Oceanica, where the meadow elements are specified by sets of microsatellite markers, then we extract the semantic flow network from a set of Wikipedia pages, showing the semantic channels between different areas of knowledge.
Cite
@article{arxiv.1009.4797,
title = {Extracting directed information flow networks: an application to genetics and semantics},
author = {A. P. Masucci and A. Kalampokis and V. M. Eguíluz and E. Hernández-García},
journal= {arXiv preprint arXiv:1009.4797},
year = {2011}
}