Modelling Weighted Signed Networks
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|Title:||Modelling Weighted Signed Networks||Authors:||Caimo, Alberto; Gollini, Isabella||Permanent link:||http://hdl.handle.net/10197/10926||Date:||20-Jun-2019||Online since:||2019-07-18T11:02:48Z||Abstract:||In this paper we introduce a new modelling approach to analyse weighted signed networks by assuming that their generative process consists of two models: the interaction model which describes the overall connectivity structure of the relations in the network without taking into account neither the weight nor the sign of the dyadic relations; and the conditional weighted signed network model describes how the edge signed weights form given the interaction structure. We then show how this modelling approach can facilitate the interpretation of the overall network process. Finally, we adopt a Bayesian inferential approach to illustrate the new methodology by modelling the Sampson’s influence network.||Type of material:||Conference Publication||Publisher:||Pearson||Start page:||111||End page:||118||Keywords:||Signed networks; Weighted networks; Exponential-family network models; Bayesian inference||Other versions:||https://mathesia.com/sis19/||Language:||en
|Status of Item:||Peer reviewed||Is part of:||Arbia, G., Peluso, S., Pini, A. & Rivellini, G. (eds.). Smart Statistics for Smart Applications, Book of Short Papers SIS 2019||Conference Details:||SIS 2019: Conference of the Italian Statistical Society Milan, 18-21 June 2019||ISBN:||9788891915108|
|Appears in Collections:||Mathematics and Statistics Research Collection|
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