We analyse bill cosponsorship networks in the Italian Chamber of Deputies. In comparison with other parliaments, a distinguishing feature of the Chamber is the large number of political groups. Our analysis aims to infer the pattern of collaborations between these groups from data on bill cosponsorships. We propose an extension of stochastic block models for edge-valued graphs and derive measures of group productivity and of collaboration between political parties. As the model proposed encloses a large number of parameters, we pursue a penalized likelihood approach that enables us to infer a sparse reduced graph displaying collaborations between political parties
This work is motivated by the analysis of multilevel networks. We define a multilevel network as the...
International audienceCommunity detection in graphs often relies on ad hoc algorithms with no clear ...
We present a study of the network of relationships among elected members of the Finnish parliament, ...
We analyse bill cosponsorship networks in the Italian Chamber of Deputies. In comparison with other ...
We analyze the network of relations between parliament members according to their voting behavior. I...
We analyze the network of relations between parliament members according to their voting behavior. I...
Despite a long tradition in the study of graphs and relational data, for decades the analysis of com...
Finding communities in complex networks is a challenging task and one promising approach is the Stoc...
Reliably learning group structures among nodes in network data is challenging in several application...
Published in at http://dx.doi.org/10.1214/10-AOAS382 the Annals of Applied Statistics (http://www.im...
Social network analysis is the study of how links between a set of actors are formed. Typically, it ...
We analyze the network of relations between parliament members according to their voting behavior. I...
International audienceA multilevel network is defined as the junction of two interaction networks, o...
Despite a long tradition in the study of graphs and relational data, for decades the analysis of com...
We propose a new methodology for inferring political actors’ latent memberships in communities of co...
This work is motivated by the analysis of multilevel networks. We define a multilevel network as the...
International audienceCommunity detection in graphs often relies on ad hoc algorithms with no clear ...
We present a study of the network of relationships among elected members of the Finnish parliament, ...
We analyse bill cosponsorship networks in the Italian Chamber of Deputies. In comparison with other ...
We analyze the network of relations between parliament members according to their voting behavior. I...
We analyze the network of relations between parliament members according to their voting behavior. I...
Despite a long tradition in the study of graphs and relational data, for decades the analysis of com...
Finding communities in complex networks is a challenging task and one promising approach is the Stoc...
Reliably learning group structures among nodes in network data is challenging in several application...
Published in at http://dx.doi.org/10.1214/10-AOAS382 the Annals of Applied Statistics (http://www.im...
Social network analysis is the study of how links between a set of actors are formed. Typically, it ...
We analyze the network of relations between parliament members according to their voting behavior. I...
International audienceA multilevel network is defined as the junction of two interaction networks, o...
Despite a long tradition in the study of graphs and relational data, for decades the analysis of com...
We propose a new methodology for inferring political actors’ latent memberships in communities of co...
This work is motivated by the analysis of multilevel networks. We define a multilevel network as the...
International audienceCommunity detection in graphs often relies on ad hoc algorithms with no clear ...
We present a study of the network of relationships among elected members of the Finnish parliament, ...