Modelling Weighted Signed Networks

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Title: Modelling Weighted Signed Networks
Authors: Caimo, AlbertoGollini, 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 networksWeighted networksExponential-family network modelsBayesian inference
Other versions: https://mathesia.com/sis19/
Language: en
it
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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