Luka Bekavac
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Item type:Publication, Scrutinizing Systemic Risks in Personalized Recommender Systems Through Sock-Puppet Auditing of VLOPs(ACM, 2026-01-30); ; ; ; Very Large Online Platforms (VLOPs) use personalized recommender systems to optimize their main performance metric: attention-based user engagement. In doing so, these systems might however amplify systemic risks by promoting controversial or polarizing content, thereby exacerbating issues such as misinformation, societal polarization, and the manipulation of civic discourse. To mitigate these risks, regulations such as the European Union's Digital Services Act (DSA) mandate increased data access and transparency, including for the auditing of personalized recommender systems. However, the data access provided by VLOPs remains limited-often restricted to specific user demographics, aggregate statistics, or curated datasets-hindering meaningful oversight. Consequently, new methods are needed to audit recommender systems effectively at the user level. In this paper, based on an analysis of the legal context and technical alternatives for data access, we present SOAP, the System for Observing and Analyzing Posts. SOAP is an open-source framework for auditing recommender systems using sock-puppet accounts. It enables fine-grained user-level analysis beyond the constrained data access typically provided by platforms. We detail SOAP's technical implementation and evaluate its ability to scrutinize systemic risks. Additionally, we tested SOAP in a workshop with over 100 participants and observed a measurable increase in participants' algorithmic literacy. This demonstrates SOAP's potential not only for research and regulatory auditing, but also as an educational framework to foster public awareness of algorithmic influence.Type:journal articleJournal:ACM Transactions on Recommender SystemsDOI:10.1145/3795516 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Connecting Personalized Realities: Challenges and Opportunities in a Personalized Society(2026-04-13); ; ; Enabled by advances in XR and AI, personalized services are increasingly affecting how individuals perceive, interact with, and navigate their realities. The resulting Personalized Realities (PR) may help people to interact more effectively with their surroundings, and allow more equitable access to information. However, PRs may also disconnect them from a collective understanding through isolated perceptions and perceptual filter bubbles. As democratic societies strive for social cohesion and shared knowledge and experiences, individual PRs may thus further add to existing social fragmentation. Yet, as PRs are framed as a concern that adapts experiences for a single user, they do not capture the full societal implications of a world where personalized mediation of reality is ubiquitous. In this paper, we therefore introduce the term Personalized Society (PSoc) to describe societies in which people predominantly access information and interact with others through a personalized mediation of reality. We discuss the duality of a PSoc, where personalization should be beneficial to the individual but at the same time connect people rather than isolate them. We identify key tensions arising in a PSoc and propose initial design considerations for fostering social cohesion alongside individual PRs, illustrating these through selected scenarios. Finally, we discuss the extent to which regulatory frameworks, such as the Digital Services Act, can be applied to protect individual and societal rights in a PSoc.Type:conference contribution - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Change Your Perspective, Widen Your Worldview! Societally Beneficial Perceptual Filter Bubbles in Personalized Reality(2025-04-26); ; ; Extended Reality (XR) technologies enable the personalized mediation of an individual's perceivable reality across modalities, thereby creating a Personalized Reality (PR). While this may lead to individually beneficial effects in the form of more efficient, more fun, and safer experiences, it may also lead to perceptual filter bubbles since individuals are exposed predominantly or exclusively to content that is congruent with their existing beliefs and opinions. This undermining of a shared basis for interaction and discussion through constrained perceptual worldviews may impact society through increased polarization and other well-documented negative effects of filter bubbles. In this paper, we argue that this issue can be mitigated by increasing individuals' awareness of their current perspective and providing avenues for development, including through support for engineered serendipity and fostering of self-actualization that already show promise for traditional recommender systems. We discuss how these methods may be transferred to XR to yield valuable tools to give people transparency and agency over their perceptual worldviews in a responsible manner.Type:conference contribution - Some of the metrics are blocked by yourconsent settings
Item type:Publication, QR Code Integrity by DesignAs QR codes become ubiquitous in various applications and places, their susceptibility to tampering, known as quishing, poses a significant threat to user security. In this paper we introduce SafeQR codes that address this challenge by introducing innovative design strategies to enhance QR code security. Leveraging visual elements and secure design principles, the project aims to make tampering more noticeable, thereby empowering users to recognize and avoid potential phishing threats. Further, we highlight the limitations of current user-education methods in combating quishing and propose different attacker models tailored to address quishing attacks. In addition, we introduce a multi-faceted defense strategy that merges design innovation with user vigilance. Through a user study, we demonstrate the efficacy of ’Integrity by Design’ QR codes. These innovatively designed QR codes significantly raise user suspicion in case of tampering and effectively reduce the likelihood of successful quishing attacks.Type:conference contributionScopus© Citations 11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, From Walls to Windows: Creating Transparency to Understand Filter Bubbles in Social Media(2024-10-18); ; ; ; Social media platforms play a significant role in shaping public opinion and societal norms. Understanding this influence requires examining the diversity of content that users are exposed to. However, studying filter bubbles in social media recommender systems has proven challenging, despite extensive research in this area. In this work, we introduce SOAP (System for Observing and Analyzing Posts), a novel system designed to collect and analyze very large online platforms (VLOPs) data to study filter bubbles at scale. Our methodology aligns with established definitions and frameworks, allowing us to comprehensively explore and log filter bubbles data. From an input prompt referring to a topic, our system is capable of creating and navigating filter bubbles using a multimodal LLM. We demonstrate SOAP by creating three distinct filter bubbles in the feed of social media users, revealing a significant decline in topic diversity as fast as in 60min of scrolling. Furthermore, we validate the LLM analysis of posts through an inter-and intra-reliability testing. Finally, we open source SOAP as a robust tool for facilitating further empirical studies on filter bubbles in social media.Type:conference contribution