Detail výsledku
Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics
Pecher Branislav, Ing., Ph.D., UPGM (FIT)
Šimko Jakub, doc. Ing., PhD., UPGM (FIT)
SRBA, I.
MÓRO, R.
ŠTEFANCOVÁ, E.
Kompan Michal, doc. Ing., PhD., UPGM (FIT)
HRČKOVÁ, A.
PODROUŽEK, J.
Bieliková Mária, prof. Ing., Ph.D., UPGM (FIT)
We investigated the creation and bursting dynamics of misinformation filter bubbles on YouTube using a black-box sockpuppeting audit technique. In this study, pre-programmed agents acting as YouTube users stimulated YouTube's recommender systems: they first watched a series of misinformation promoting videos (bubble creation) and then a series of misinformation debunking videos (bubble bursting). Meanwhile, agents recorded videos recommended to them by YouTube. After manually annotating these recommendations, we were able to quantify the portion of misinformative videos among them. The results confirm the creation of filter bubbles (albeit not in all situations) and show that these bubbles can be bursted by watching credible content. Drawing a direct comparison with a previous study, we do not see improvements in overall quantities of misinformation recommended.
Black boxes, Bubble bursting, Bubble dynamics, Extended abstracts, YouTube
@inproceedings{BUT180393,
author="TOMLEIN, M. and PECHER, B. and ŠIMKO, J. and SRBA, I. and MÓRO, R. and ŠTEFANCOVÁ, E. and KOMPAN, M. and HRČKOVÁ, A. and PODROUŽEK, J. and BIELIKOVÁ, M.",
title="Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics",
booktitle="Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence Sister Conferences Best Papers",
year="2022",
pages="5349--5353",
publisher="International Joint Conferences on Artificial Intelligence",
address="Vienna",
doi="10.24963/ijcai.2022/749",
isbn="978-1-956792-00-3",
url="https://www.ijcai.org/proceedings/2022/749"
}