  YouTube is a major social media platform that plays a significant role in
digital culture, with content creators at its core. These creators often engage
in controversial behaviour to drive engagement, which can foster toxicity. This
paper presents a quantitative analysis of controversial content on YouTube,
focusing on the relationship between controversy, toxicity, and monetisation.
We introduce a curated dataset comprising 20 controversial YouTube channels
extracted from Reddit discussions, including 16,349 videos and more than 105
million comments. We identify and categorise monetisation cues from video
descriptions into various models, including affiliate marketing and direct
selling, using lists of URLs and keywords. Additionally, we train a machine
learning model to measure the toxicity of comments in these videos. Our
findings reveal that while toxic comments correlate with higher engagement,
they negatively impact monetisation, indicating that controversy-driven
interaction does not necessarily lead to financial gain. We also observed
significant variation in monetisation strategies, with some creators showing
extensive monetisation despite high toxicity levels. Our study introduces a
curated dataset, lists of URLs and keywords to categorise monetisation, a
machine learning model to measure toxicity, and is a significant step towards
understanding the complex relationship between controversy, engagement, and
monetisation on YouTube. The lists used for detecting and categorising
monetisation cues are available on https://github.com/thalesbertaglia/toxmon.
