POLARIDAD DE LAS OPINIONES EN REDES SOCIALES APLICADA A LA CLASIFICACIÓN DE LOS SERVICIOS UNIVERSITARIOS

Abstract

The present research fulfills the objective of using the Big Data generated through the opinions of the social networks of the Institutions of Higher Education, which are free of biases when manifesting about the IT services offered by these institutions, providing a bank of data that serves as raw material for data mining and text that is used to guide the ITIL process in its Service Strategy phase. The mining process uses the methodology known as CRISP - DM that obtains values that determine the quality of the service studied, giving an input for the decision making that will allow to maintain, improve or eliminate the IT service analyzed. Finally, it is concluded that using social networks to know the opinions of the IT services offered by the institutions and at the same time applying a mining process to guide the adaptation of ITIL best practices is a reliable process because the users feel in the freedom to comment on the service received.