ALGORITHMIC GOVERNANCE: A QUALITATIVE INVESTIGATION INTO NEWS PERSONALIZATION
Algorithmic Governmentality; Journalism; Mediatization; News personalization
The research investigates how the algorithmic personalization of news, driven by Algorithmic Governmentality (Rouvroy; Berns, 2015), through mechanisms such as data collection and analysis, dataveillance and datamining respectively, shapes news consumption and impacts the traditional values of journalism. We argue that the practice, although it offers convenience, can lead to the formation of filter bubbles (Pariser, 2012), limiting exposure to different perspectives and influencing opinion formation. The research methodology is qualitative (Minayo, 2002; Duarte, 2006; Fígaro, 2014), using in-depth interviews with journalists from different vehicles in the Northeast region of Brazil, seeking to understand how professionals in the field deal with new technologies and their impacts in the production and consumption of news. From the analysis of the data collected, we shed light on the challenges and ethical implications (Sodré, 2021) of algorithmic personalization in contemporary journalism (Gillespie, 2018), in a context of profound mediatization (Couldry; Hepp, 2020) and growing influence of algorithms in society.