Implementação e integração de uma arquitetura de software para um crawler de postagens em plataformas digitais

Abstract

The study addresses the issue of misinformation on social networks, a phenomenon exacerbated by artificial intelligence technologies and mass dissemination strategies, which undermine the credibility of democratic processes and the formation of public opinion. The research proposes a technical solution to automate the collection and analysis of data from fact-checking agencies and digital platforms, employing crawlers and APIs, with a focus on integration with the Web 3.0 Project. The results demonstrated the effectiveness of the developed architecture in consolidating structured data from reliable sources and social networks, enabling analyses such as sentiment analysis to identify polarizations and social trends. Despite limitations imposed by social network APIs, the system proved scalable and functional, contributing to a more agile and accessible fight against misinformation. Thus, the study highlights the importance of integrating technology and human expertise to tackle complex informational challenges.