Artificial intelligence applied in the detection of hate speech in the social political context in early 2023 in Peru

Abstract

The rapid spread of hate speech through social networks to a large number of people has generated destabilization in a social and economic context at the beginning of the year 2023. The purpose of the research is to detect hate speech through Artificial Intelligence with Machine Learning techniques in a social political context. In addition, the research is of an applied type in which an exploratory search was carried out and the population is comprised of 1,970 tweets in the central and southern regions of Peru. The sampling is probabilistic, and 1,970 tweets from the regions involved were reviewed and manually labeled. Likewise, the methodology applied was SEMMA, as it allows to ensure that the models are accurate and fit the data of this study. A comparison of the respective models was performed to achieve an optimal result, of which the main indicator was the average accuracy in which the Multinomial Naive Bayes model was the best model with a score of 73.87%. Finally, it is concluded that this study allows accelerating the process of detecting verbal hate speech in social networks for the analysis of public opinion and the detection of suspected hate inciters.