Algorithmic governance and its influence on the perception of the Judiciary on social media.
Algorithmic governance; Social media perception; Judiciary
Social media has emerged as spaces for debate capable of influencing public perception of institutions, including the Judiciary. In Brazil, where over 61% of the population is active on social media, understanding how algorithmic governance shapes perceptions is essential. In this regard, the research problem consists of understanding how
algorithmic governance, manifested through social media recommendation algorithms, influences the civic and discursive behavior of users of these platforms in relation to the Judiciary. The general hypothesis is that algorithmic governance contributes to the formation of "filter bubbles", affecting opinion polarization and the perception of the Judiciary's legitimacy. The methodology involves data collection on social media, graph analysis for community detection, semantic analysis, sentiment analysis of posts, and the development of a Polarization Index (PI). From these analyses, we expect to identify dominant symbols on social media that influence perceptions of the Judiciary, assess the impact of algorithms on the formation of "filter bubbles", and propose strategies for the Judiciary to engage proactively in digital discourse more effectively. Expected results include quantifying the impact of recommendation algorithms on the creation of "filter bubbles", identifying predominant narratives, and suggesting strategies for the Judiciary to address the challenges posed by algorithmic governance.