Analysis of the social impact of the community info-centers in the canton La Maná-Ecuador

Abstract

The prediction of the social impact of the community infocenters is relevant for the person in charge, the users and the administrators, when generating precise information about the educational situation, the digital inclusion, the technological appropriation, social participation, from the recognition of the benefits and opportunities for services, as well as helping to choose more efficient communication tools to manage information and knowledge according to personal and community needs, interest and motivation. For the users of the community, it is relevant when communicating with other people, relatives, with community services. In this work the analysis of the social impact caused by the implementation of community infocenters in the Canton La Maná using artificial intelligence techniques was carried out. For this purpose, artificial intelligence and data mining algorithms are used. These algorithms are implemented in a computational tool for machine learning, called Weka. In addition, the varieties of techniques and algorithms, and their respective advantages, analyzed in this study, about the Weka tool allow identifying the potentials to be used in the determination of predictions of transformations in organizations that offer services to society in general. The experimental results showed that these algorithms have a good performance for the prediction of social impact. Based on this case study, it is concluded that the Kstar algorithm shows the best performance with our dataset.