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Fernando Thompson, Universidade Nova de Lisboa, PortugalAbstract
This paper investigates how algorithms asymmetrically influence the digital journeys of users across different cities and platforms. Building upon Pariser’s (2011) framework advocating for research that incorporates geolocation, cross-platform analysis, and non-logged-in user experiences, this study adopts a mixed-methods approach. Quantitative data was gathered from 705 anonymous participants in São Paulo, Lisbon, and New York, with 457 valid responses (64.8% response rate), an 8% margin of error, and a 95% confidence level. Qualitative insights were drawn from semi-structured interviews coded in NVivo. Findings indicate contextual differences in algorithmic mediation. São Paulo users reported greater difficulty escaping algorithmic filter bubbles, while New York participants demonstrated fluid cross-platform navigation. Lisbon users expressed stronger critical awareness of automated curation. Platforms like YouTube, with continuous recommendation systems, were found to amplify informational echo chambers and confirmation biases, particularly among São Paulo users. Conversely, search-based tools such as Google were perceived as more neutral; however, quantitative analysis revealed latent personalization mechanisms operating even in non-logged-in sessions—suggesting invisible algorithmic steering. By integrating technical, cultural, and territorial dimensions, this research expands the concept of the "digital journey" as a contextually situated and unevenly mediated experience. It contributes to the growing interdisciplinary field of algorithmic governance by shedding light on the sociotechnical dynamics affecting user autonomy and perception across diverse urban environments.
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