Resumen en inglés

In this graduate work, an analysis of the incidence of social networks on the emotions of students at the University of Cordoba was carried out. For this purpose, a web application was used to identify the type of emotions and the perception of students in relation to topics exposed in Instagram publications. Web Scraping and Natural Language Processing Analysis tools were used to examine the comments made by students on a selection of publications. These publications address various topics classified by category, with the aim of obtaining the emotional perception of students in front of different topics. The RUP (Rational Unified Process) methodology was applied, which made it possible to establish a solid architectural base and reduce the impact of subsequent changes in the system. The system was developed using different technologies in each section of the project. The Angular, Express and Flask frameworks were used, the first one for Frontend, the next two for backend. A total of 30 samples were studied, in which it was found that publications related to human expression and skills development generate positive emotions and polarities, contrary to publications about news dissemination and educational opportunities. On the other hand, positive correlations were identified, one between positive polarity and the emotion of joy and another between negative polarity and emotions such as anger, sadness and neutral.