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We conduct a preliminary analysis of comments on political YouTube contentcontaining misinformation in comparison to comments on trustworthy orapolitical videos, labelling the bias and factual ratings of our channelsaccording to Media Bias Fact Check where applicable. One of our mostinteresting discoveries is that especially-polarized or misinformativepolitical channels (Left-Bias, Right-Bias, PragerU, Conspiracy-Pseudoscience,and Questionable Source) generate 7.5x more comments per view and 10.42x morereplies per view than apolitical or Pro-Science channels; in particular,Conspiracy-Pseudoscience and Questionable Sources generate 8.3x more commentsper view and 11.0x more replies per view than apolitical and Pro-Sciencechannels. We also compared average thread lengths, average comment lengths, andprofanity rates across channels, and present simple machine learningclassifiers for predicting the bias category of a video based on thesestatistics.

YouTube Chatter: Understanding Online Comments Discourse on Misinformative and Political YouTube Videos