1 research outputs found
Community detection problem based on polarization measures:an application to Twitter: the COVID-19 case in Spain
In this paper, we address one of the most important topics in the field of
Social Networks Analysis: the community detection problem with additional
information. That additional information is modeled by a fuzzy measure that
represents the risk of polarization. Particularly, we are interested in dealing
with the problem of taking into account the polarization of nodes in the
community detection problem. Adding this type of information to the community
detection problem makes it more realistic, as a community is more likely to be
defined if the corresponding elements are willing to maintain a peaceful
dialogue. The polarization capacity is modeled by a fuzzy measure based on the
JDJpol measure of polarization related to two poles. We also present an
efficient algorithm for finding groups whose elements are no polarized.
Hereafter, we work in a real case. It is a network obtained from Twitter,
concerning the political position against the Spanish government taken by
several influential users. We analyze how the partitions obtained change when
some additional information related to how polarized that society is, is added
to the problem.Comment: 27 page