Dear all,

I hope to find you well 🙂

We have a very special event: an (online) seminar of our young Mattia Mattei (TOFFEe project) today at 11.30. The link to the seminar is here: https://meet.google.com/ito-gwkx-byc

The title of his talk is An entropy-based perspective on Online Social Networks: semantic networks and bow-tie structures.
Abstract: My presentation will focus on two different applications of entropy-based models to the analysis of Online Social Networks, specifically Twitter. The first part of the meeting will be dedicated to the analysis of the Twitter semantic network during the Italian Covid-19 epidemic. Using as a benchmark an entropy-based bipartite configuration model (BiCM, [1]), we constructed a bipartite network of users and hashtags, related to the Italian online debate about the epidemic, following a strategy similar to the one developed in [2]. We observed that the debate is mainly political, even if the subject is not exclusively so. Remarkably, the observed discursive communities are not equally exposed to d/misinformation campaigns, as can be observed by considering the communities of hashtags related to false information about the origin of the COVID-19 pandemic, confirming previous findings [3].In the second work we characterise the network structure of the discursive communities. The bow-tie structure was initially introduced by Broder et al. [4] in order to study the World Wide Web, dividing, mainly, the entire system in a Strongly Connected Component (SCC) of all websites, in a IN block, including all search engines and an OUT block composed by the authorities (i.e. Wikipedia). Remarkably, the same structure is almost ubiquitous in the discursive communities on Twitter that focus on political subjects: we analyse 8 different discussions in different languages and a strong bow-tie structure is almost always present in many political discoursive communities, while it is absent in other different debates. We further characterize the various groups and blocks in the network. 

[1] Saracco et al, Scientific Reports (2016)
[2] Radicioni et al, arXiv:2009.02960 (2020)
[3] Caldarelli et al, arXiv:2010.01913 (2020)
[4] Broder et al, Computer Networks (2000) 

Be there and stay tuNedo!

Nedo