1 research outputs found
Social Relevance Index for Studying Communities in a Facebook Group of Patients
Identifying Relevant Sets, i.e., variable subsets that exhibit
a coordinated behavior, in complex systems is a very relevant research
topic. Systems that exhibit complex dynamics are, for example, social
networks, which are characterized by complex and dynamic relationships
among users. A challenging topic within this context regards the
identification of communities or subsets of users, both within the whole
network and within specific groups. We applied the Relevance Index
method, which has been shown to be effective in many situations, to the
study of communities of users in the Facebook group of the Italian association
of patients affected by Hidradenitis Suppurativa. Since the need
for computing the Relevance Index for each possible variable subset of
users makes the exhaustive computation unfeasible, we resorted to the
help of an efficient niching evolutionary metaheuristic, hybridized with
local searches. The communities detected through the aforementioned
method have been studied to search similarities in terms of number of
posts, sentiments, number of contacts, roles, behaviors, etc. The results
demonstrate that it is possible to detect such subsets of users in the
particular Facebook group we analyzed