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Model of Classification of University Services Using the Polarity of Opinions Taken from Social Networks

Abstract:

The objective of this research is to use the Big Data generated through the opinions of the social networks of Higher Education Institutions, which are free from bias at the time of expressing themselves about the IT services offered by these institutions, providing a data bank that serves as raw material to perform a data and text mining that is used to guide the ITIL process in its phase of Service Strategies. 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 decision making that will 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 apply a mining process to guide the adaptation of ITIL best practices is a reliable process because users feel free to express their opinion about the service received.