São João do Maranhão: análise de tópicos e sentimentos em tweets e notícias

Abstract

The growing percentage of the population with internet access in Brazil means that social media such as X is being used more frequently and, consequently, text data generated by its users is becoming more available. Therefore, it is interesting to collect text samples from users and analyze opinions on a given topic. In this study, sentiment analysis and topic modeling were performed using data from X and G1 about São João do Maranhão during the 2023 and 2024 festivities. The objective was to identify the impression left by the event on the population of Maranhão. To this end, web scraping techniques were applied to collect data. In total, 1,756 tweets and 125 news items were collected. After collection, the texts underwent pre-processing methods to allow sentiment classiĄcation and topic modeling. To identify the topics covered in social media, BERTopic was used, which was successful in identifying the main topics covered by Internet users, such as: São João da Thay, Bumba Meu Boi, art and folklore. Regarding sentiment analysis, it was found that the vast majority of tweets and articles published by G1 were positive, conĄrming the broad satisfaction of users in relation to São João do Maranhão.