[Forum SIS] Fwd: {Disarmed} Riccardo Faini CEIS Seminars - 20 April 2018

[Roberto Rocci]

Cari colleghi,
vi inoltro il seguente avviso riguardo un seminario che il collega
Bartolucci
terrà presso la Facoltà di Economia di Tor Vergata il 20 aprile p.v.

Saluti,
Roberto Rocci



Francesco Bartolucci
Riccardo Faini CEIS Seminars
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*Dealing with Reciprocity in Dynamic Stochastic Block Models*


*Francesco Bertolucci
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University of Perugia*


*20 April 2018 h.12:00 Room B - 1st floor*

*joint work with F.M. Marino and S.Pandolfi*

A stochastic block model for dynamic network data is introduced, where
directed relations among a set of nodes are observed at different time
occasions and the blocks are represented by a sequence of latent variables
following a Markov chain. Dyads are explicitly modeled conditional on the
states occupied by both nodes involved in the relation. With respect to the
approaches already available in the literature, the main focus is on
reciprocity. In this regard, three different parameterizations are proposed
in which: (i) reciprocity is allowed to depend on the blocks of the nodes
in the dyad; (ii) reciprocity is assumed to be constant across blocks; and
(iii) reciprocity is ruled out. The assumption of conditional independence
between dyads (referred to different pairs of nodes and time occasions)
given the latent blocks is always retained. Given the complexity of the
model, inference on its parameters is based on a variational approach,
where a lower bound of the log-likelihood function is maximized instead of
the intractable full model log-likelihood.
An approximate likelihood ratio test statistic is proposed which compares
the value at convergence of this lower bound under different model
specifications. This allows us to formally test for both the hypothesis of
no reciprocity and that of constant reciprocity with respect to the latent
blocks. The proposed approach is illustrated via a simulation study based
on different scenarios. The application to two benchmark datasets in the
social network literature is also proposed to illustrate the effectiveness
of the proposal in studying reciprocity and identifying groups of nodes
having a similar social behavior.



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reserved.*
Riccardo Faini CEIS Seminar

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