Characterizing Abhorrent, Misinformative, and Mistargeted Content on YouTube
Kostantinos Papadamou

TL;DR
This paper analyzes problematic content on YouTube, including disturbing videos for children, misogynistic content from Incels, and pseudoscientific misinformation, highlighting the platform's role in promoting such content through its recommendation algorithm.
Contribution
It provides a comprehensive data-driven analysis of how YouTube's recommendation system disseminates harmful and misleading content across different user scenarios.
Findings
Young children are likely to encounter disturbing content randomly.
Incel activity on YouTube is increasing over time.
Pseudoscientific content is more suggested on search results than on homepage or recommendations.
Abstract
YouTube has revolutionized the way people discover and consume video. Although YouTube facilitates easy access to hundreds of well-produced and trustworthy videos, abhorrent, misinformative, and mistargeted content is also common. The platform is plagued by various types of problematic content: 1) disturbing videos targeting young children; 2) hateful and misogynistic content; and 3) pseudoscientific misinformation. While YouTube's recommendation algorithm plays a vital role in increasing user engagement and YouTube's monetization, its role in unwittingly promoting problematic content is not entirely understood. In this thesis, we shed some light on the degree of problematic content on YouTube and the role of the recommendation algorithm in the dissemination of such content. Following a data-driven quantitative approach, we analyze thousands of videos on YouTube, to shed light on: 1)…
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Taxonomy
TopicsMisinformation and Its Impacts · Media Influence and Politics · Hate Speech and Cyberbullying Detection
