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  • Code-Dependency : Tiktok's AI & suggested content feed. Users circumstances to go outside of their filter bubbles
    Publication . Tiraborelli, Alice; Tavares, Patrícia Isabel Ramos Pego Nunes
    This dissertation's main objective is to understand users' perceived usage of TikTok's algorithm, particularly focusing on their reasons for exploring content beyond the platform's suggested feed. This exploratory study aims to look into user search behavior concerning algorithmic recommendations. To gain a comprehensive understanding, the theoretical framework addresses three key areas: the concept of "Platform Society," the role of artificial intelligence (AI) and algorithms in social media, and the phenomenon of "Algorithmic Sovereignty." With this theoretical approach, this research addresses user interactions on TikTok by examining how users navigate and engage with the platform's algorithmically curated content, versus actively searching for content independently. Through a detailed examination of TikTok's algorithm, user behavior, and engagement strategies, the study provides insights into the interplay between user agency and algorithmic control. Findings indicate that TikTok's algorithm significantly influences user behavior by personalizing content feeds based on user interactions, preferences, and engagement patterns. The study reveals that while many users rely heavily on algorithmically suggested content, some actively seek diverse content, demonstrating varying degrees of algorithmic awareness. The algorithm's influence is most evident in shaping user engagement and interaction patterns, guiding content discovery, and reinforcing specific content preferences. Moreover, the study identifies a complex relationship between user agency and algorithmic influence, highlighting the need for greater transparency and user awareness in navigating algorithmically mediated environments. The implications of these findings extend to understanding digital behavior on social media platforms, emphasizing the importance of balancing algorithmic personalization with user autonomy. Ultimately, this dissertation contributes to the broader discourse on the societal impact of AI and algorithms, advocating for strategies that enhance user empowerment in the digital age.
    2025-05-08Master thesis Embargoed access Show more