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Internal seminars: "Bayesian finite mixture model with overlapping clusters for the analysis of a terrorist network data"

07/02/2017 dalle 13:15 alle 14:00

Dove Dipartimento di Scienze Statistiche "P. Fortunati" - Via Belle Arti 41 - Aula III

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Saverio Ranciati
Research fellow - Dipartimento di Scienze Statistiche Bologna


Network data usually summarize information about the relationships between individuals and their interactions as communities. Their social behaviours are used to understand which features tie them together, providing an insight about the group structure of the whole network by detecting the link connecting each unit. In some cases, these intertwined dynamics are characterized by records of individuals (actors) attending to events. A common approach is to project actor-events data into an actor-actor setting, which sometimes provides biased and contaminated answers. We focus instead on a model-based clustering approach that encodes the natural actor-events representation of the data, allowing for observations to be assigned to (potentially) more than one community via a Bayesian finite mixture model with multiple allocations. The driving research question is to understand the group structure of a terrorist network dataset, where recordings of militants and their attendance to different meetings and operations are available.

Alessandra Luati
Silvia Cagnone