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Activity Number: 95 - Network Data Analysis
Type: Topic Contributed
Date/Time: Monday, August 8, 2022 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract #322484
Title: Continuous Latent Position Network Models
Author(s): Riccardo Rastelli* and Marco Corneli
Companies: University College Dublin and Université Côte d'Azur
Keywords: Network Analysis; Latent Position Models; Dynamic Networks; Spatial Embedding
Abstract:

We create a framework to analyse the timing and frequency of instantaneous interactions between pairs of entities. Nowadays, this type of time-stamped interaction data is especially common in many applied fields. Examples include email networks, phone call networks, proximity networks. The framework that we introduced is inspired by latent position network models: the entities are embedded in a continuous latent Euclidean space, and they move along individual trajectories that are also continuous over time. These trajectories are used to model the timing and frequency of the pairwise interactions. We discuss an inferential framework where we estimate the trajectories from the observed interaction data, and propose applications on artificial and real data.


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