@Article{SilvaBrViRoMoCoFr:2016:SoNeAn,
author = "Silva, Aleksandra do Socorro da and Brito, Silvana Rossy de and
Vijaykumar, Nandamudi Lankalapalli and Rocha, Cl{\'a}udio Alex
Jorge da and Monteiro, Maur{\'{\i}}lio de Abreu and Costa,
Jo{\~a}o Cris{\'o}stomo Weyl Albuquerque and Franc{\^e}s,
Carlos Renato Lisboa",
affiliation = "{Federal Rural University of Amazon} and {Federal Rural University
of Amazon} and {Instituto Nacional de Pesquisas Espaciais (INPE)}
and Federal Institute of Education, Science and Technology of
Par{\'a} and {Federal University of Par{\'a}} and {Federal
University of Par{\'a}} and {Federal University of Par{\'a}}",
title = "Social network analysis and mining to monitor and identify
problems with large-scale information and communication technology
interventions",
journal = "PLoS One",
year = "2016",
volume = "11",
number = "1",
pages = "e0146220",
month = "Jan.",
abstract = "The published literature reveals several arguments concerning the
strategic importance of information and communication technology
(ICT) interventions for developing countries where the digital
divide is a challenge. Large-scale ICT interventions can be an
option for countries whose regions, both urban and rural, present
a high number of digitally excluded people. Our goal was to
monitor and identify problems in interventions aimed at
certification for a large number of participants in different
geographical regions. Our case study is the training at the
Telecentros. BR, a program created in Brazil to install
telecenters and certify individuals to use ICT resources. We
propose an approach that applies social network analysis and
mining techniques to data collected from Telecentros. BR dataset
and from the socioeconomics and telecommunications infrastructure
indicators of the participants' municipalities. We found that (i)
the analysis of interactions in different time periods reflects
the objectives of each phase of training, highlighting the
increased density in the phase in which participants develop and
disseminate their projects; (ii) analysis according to the roles
of participants (i. e., tutors or community members) reveals that
the interactions were influenced by the center (or region) to
which the participant belongs (that is, a community contained
mainly members of the same region and always with the presence of
tutors, contradicting expectations of the training project, which
aimed for intense collaboration of the participants, regardless of
the geographic region); (iii) the social network of participants
influences the success of the training: that is, given evidence
that the degree of the community member is in the highest range,
the probability of this individual concluding the training is
0.689; (iv) the North region presented the lowest probability of
participant certification, whereas the Northeast, which served
municipalities with similar characteristics, presented high
probability of certification, associated with the highest degree
in social networking platform.",
doi = "10.1371/journal.pone.0146220",
url = "http://dx.doi.org/10.1371/journal.pone.0146220",
issn = "1932-6203",
language = "en",
urlaccessdate = "27 abr. 2024"
}