Responsible use of user data by Meta company: data protection and the impact on the formation of thought bubbles

Abstract

This study examines Meta's data collection, usage, and sharing practices in light of the General Data Protection Law (LGPD) and the "filter bubbles" theory. Adopting a mixed-methods approach (qualitative and quantitative), the research combines documental and bibliographic analysis with textual frequency algorithms to explore privacy policies and the impact of personalization algorithms. The LGPD and Meta's privacy policies were analyzed, focusing on data collection and its use in personalization algorithms. The results indicate that, despite efforts to comply with the legislation, data monetization practices contradict transparency and privacy principles, contributing to the formation of "bubbles." Scientific publications post-2020 emphasize the relevance of the topic in areas such as Fake News and Artificial Intelligence. The study concludes that it is essential to balance innovation, data protection, and informational diversity, promoting ethical data use in light of challenges related to the formation of "filter bubbles".