Fechar
Metadados

@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 = "30 nov. 2020"
}


Fechar