%0 Generic %1 Bianconi2008 %A Bianconi, Ginestra %A Pin, Paolo %A Marsili, Matteo %D 2008 %K Social_Networks imported social-network %T How relevant are features for network structure? %U http://arxiv.org/abs/0810.4412 %X Networks describe a variety of interacting complex systems in social science, biology and information technology. Usually the nodes of real networks are not only identified by their connections but also by some other characteristics. Examples of characteristics of nodes can be age, gender or nationality of a person in a social network, the abundance of proteins in the cell taking part to a protein-interaction networks or the geographical position of airports that are connected by directed flights. Integrating the information on the connections of each node with the information about its characteristics is crucial for discriminating between essential and negligible characteristics of nodes for the structure of the network. In this paper we propose a general indicator Theta, based on entropy measures, to quantify the dependence of network's structure on a given set of features. We apply this method to social networks of friendships in US schools, to the protein-interaction network of Saccharomyces cerevisiae and to the US airport network, showing that the proposed measure provides complementary information with respect to other known measures. Comment: (7 pages, 6 figures)

@misc{Bianconi2008, abstract = { Networks describe a variety of interacting complex systems in social science, biology and information technology. Usually the nodes of real networks are not only identified by their connections but also by some other characteristics. Examples of characteristics of nodes can be age, gender or nationality of a person in a social network, the abundance of proteins in the cell taking part to a protein-interaction networks or the geographical position of airports that are connected by directed flights. Integrating the information on the connections of each node with the information about its characteristics is crucial for discriminating between essential and negligible characteristics of nodes for the structure of the network. In this paper we propose a general indicator Theta, based on entropy measures, to quantify the dependence of network's structure on a given set of features. We apply this method to social networks of friendships in US schools, to the protein-interaction network of Saccharomyces cerevisiae and to the US airport network, showing that the proposed measure provides complementary information with respect to other known measures. Comment: (7 pages, 6 figures)}, added-at = {2009-08-01T22:00:59.000+0200}, author = {Bianconi, Ginestra and Pin, Paolo and Marsili, Matteo}, biburl = {https://www.bibsonomy.org/bibtex/2be7c7a96212aec94640cd28352b9c1dc/gwpl}, description = {the importance of node features in a network - seems to support semweb approaches (but i didnt read it yet;)}, interhash = {b71c3c000163b7499e4c06ad969b2acd}, intrahash = {be7c7a96212aec94640cd28352b9c1dc}, keywords = {Social_Networks imported social-network}, timestamp = {2009-08-01T22:00:59.000+0200}, title = {How relevant are features for network structure?}, url = {http://arxiv.org/abs/0810.4412}, year = 2008 }