Processamento de linguagem natural aplicado a notícias futebolísticas

Abstract

Natural Language Processing (NLP) is an important set of techniques and tools suitable for text analysis and, when combined with the efficient use of data collection procedures from the internet, web scraping, they form effective processes for their analysis. In the context of football, sports news plays a significant role in events, as it describes and, in many cases, causes such facts. Analyzing these texts results in significant indicators about football-related events, as they reflect the desires and thoughts of fans. Furthermore, from a temporal perspective, it is possible to distinguish when an event impacts the football world, either through an increase in the number of news articles or through the strengthening of relationships between one word and another. With this in mind, analyzing the similarity between players and coaches and their respective clubs and national teams leads to conclusions regarding how impactful an event was for the audience that follows the sport. Thus, through news articles, it is possible to obtain relevant indicators from the end of 2023 until the penultimate quarter of 2025. For example, the fact that the player Neymar transferred to Santos corroborated his media exposure, and with Messi moving to play in the United States, rumors of his retirement increased, as the spotlight is no longer focused on the player. In addition, titles significantly increase a club’s appearance in the media, such as Botafogo’s victories in the Brazilian Championship and the Copa Libertadores at the end of 2024. These and other events impact the football world, and it is possible to analyze this through this type of data, namely, news articles..