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

57 citations

Showing 2022Show all

8 papers · 1 filter

cs.CY2022★ 2 cited

Autonomation, Not Automation: Activities and Needs of European Fact-checkers as a Basis for Designing Human-Centered AI Systems

Andrea Hrckova, Robert Moro, Ivan Srba +2

To mitigate the negative effects of false information more effectively, the development of Artificial Intelligence (AI) systems to assist fact-checkers is needed. Nevertheless, the…

cs.IR2022★ 57 cited

Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles

Ivan Srba, Robert Moro, Matus Tomlein +8

In this paper, we present results of an auditing study performed over YouTube aimed at investigating how fast a user can get into a misinformation filter bubble, but also what it t…

cs.LG2022

Pessimistic Off-Policy Optimization for Learning to Rank

Matej Cief, Branislav Kveton, Michal Kompan

Off-policy learning is a framework for optimizing policies without deploying them, using data collected by another policy. In recommender systems, this is especially challenging du…

cs.LG2022★ 3 cited

Towards Symbolic Time Series Representation Improved by Kernel Density Estimators

Matej Kloska, Viera Rozinajova

This paper deals with symbolic time series representation. It builds up on the popular mapping technique Symbolic Aggregate approXimation algorithm (SAX), which is extensively util…

cs.CL2022★ 31 cited

Automatic question generation based on sentence structure analysis using machine learning approach

Miroslav Blšták, Viera Rozinajová

Automatic question generation is one of the most challenging tasks of Natural Language Processing. It requires "bidirectional" language processing: firstly, the system has to under…

cs.CL2022★ 14 cited

Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims

Ivan Srba, Branislav Pecher, Matus Tomlein +4

False information has a significant negative influence on individuals as well as on the whole society. Especially in the current COVID-19 era, we witness an unprecedented growth of…

cs.IR2022★ 57 cited

An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes

Matus Tomlein, Branislav Pecher, Jakub Simko +7

The negative effects of misinformation filter bubbles in adaptive systems have been known to researchers for some time. Several studies investigated, most prominently on YouTube, h…

cs.IR2022★ 18 cited

Exploring Customer Price Preference and Product Profit Role in Recommender Systems

Michal Kompan, Peter Gaspar, Jakub Macina +2

Most of the research in the recommender systems domain is focused on the optimization of the metrics based on historical data such as Mean Average Precision (MAP) or Recall. Howeve…