  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) the
risks of YouTube media consumption by young children; 2) the role of the
recommendation algorithm in the dissemination of misogynistic content, by
focusing on the Involuntary Celibates (Incels) community; and 3) user exposure
to pseudoscientific content on various parts of the platform and how this
exposure changes based on the user's watch history. Our analysis reveals that
young children are likely to encounter disturbing content when they randomly
browse the platform. By analyzing the Incel community on YouTube, we find that
Incel activity is increasing over time and that platforms may play an active
role in steering users towards extreme content. Finally, when studying
pseudoscientific misinformation, we find that YouTube suggests more
pseudoscientific content regarding traditional pseudoscientific topics (e.g.,
flat earth) than for emerging ones (like COVID-19) and that these
recommendations are more common on the search results page than on a user's
homepage or the video recommendations section.
