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20212026
most citedAuditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles

57 citations

Showing 2025Show all

7 papers · 1 filter

cs.CR2025

Clustering Malware at Scale: A First Full-Benchmark Study

Martin Mocko, Jakub Ševcech, Daniela Chudá

Recent years have shown that malware attacks still happen with high frequency. Malware experts seek to categorize and classify incoming samples to confirm their trustworthiness or…

cs.CL2025

Political Leaning and Politicalness Classification of Texts

Matous Volf, Jakub Simko

This paper addresses the challenge of automatically classifying text according to political leaning and politicalness using transformer models. We compose a comprehensive overview…

cs.IR2025★ 2 cited

Riding the Carousel: The First Extensive Eye Tracking Analysis of Browsing Behavior in Carousel Recommenders

Santiago de Leon-Martinez, Robert Moro, Branislav Kveton +1

Carousels have become the de-facto standard user interface in online services. However, there is a lack of research in carousels, particularly examining how recommender systems may…

cs.HC2025★ 3 cited

Eye Movements as Indicators of Deception: A Machine Learning Approach

Valentin Foucher, Santiago de Leon-Martinez, Robert Moro

Gaze may enhance the robustness of lie detectors but remains under-studied. This study evaluated the efficacy of AI models (using fixations, saccades, blinks, and pupil size) for d…

cs.IR2025★ 4 cited

RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces

Santiago de Leon-Martinez, Jingwei Kang, Robert Moro +4

Carousel interfaces are widely used in e-commerce and streaming services, but little research has been devoted to them. Previous studies of interfaces for presenting search and rec…

cs.IR2025★ 3 cited

Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings

Matej Mosnar, Adam Skurla, Branislav Pecher +5

Social media platforms are constantly shifting towards algorithmically curated content based on implicit or explicit user feedback. Regulators, as well as researchers, are calling…

cs.CL2025★ 2 cited

Beyond speculation: Measuring the growing presence of LLM-generated texts in multilingual disinformation

Dominik Macko, Aashish Anantha Ramakrishnan, Jason Samuel Lucas +4

Increased sophistication of large language models (LLMs) and the consequent quality of generated multilingual text raises concerns about potential disinformation misuse. While huma…