Modelling weighted signed networks

Alberto Caimo, Isabella Gollini

Research output: Contribution to conferencePaperpeer-review

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.
Original languageEnglish
DOIs
Publication statusPublished - 2019
EventConference of the Italian Statistical Society -
Duration: 1 Jan 2019 → …

Conference

ConferenceConference of the Italian Statistical Society
Period1/01/19 → …

Keywords

  • weighted signed networks
  • interaction model
  • conditional weighted signed network model
  • Bayesian inferential approach
  • Sampson’s influence network

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