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from the can't-we-all-just-get-along? dept.
From a recent Science Reports paper:
Online debates are often characterised by extreme polarisation and heated discussions among users. The presence of hate speech online is becoming increasingly problematic, making necessary the development of appropriate countermeasures. In this work, we perform hate speech detection on a corpus of more than one million comments on YouTube videos through a machine learning model, trained and fine-tuned on a large set of hand-annotated data.
Our analysis shows that there is no evidence of the presence of "pure haters", meant as active users posting exclusively hateful comments. Moreover, coherently with the echo chamber hypothesis, we find that users skewed towards one of the two categories of video channels (questionable, reliable) are more prone to use inappropriate, violent, or hateful language within their opponents' community.
Interestingly, users loyal to reliable sources use on average a more toxic language than their counterpart. Finally, we find that the overall toxicity of the discussion increases with its length, measured both in terms of the number of comments and time. Our results show that, coherently with Godwin's law, online debates tend to degenerate towards increasingly toxic exchanges of views.
Journal Reference:
M. Cinelli, A. Pelicon, I. Mozetič, et al. Dynamics of online hate and misinformation. [open] Sci Rep 11, 22083 (2021).
DOI: 10.1038/s41598-021-01487-w
(Score: 2) by looorg on Thursday November 18 2021, @02:24PM
So this whole thing is based on comments of Italian youtube videos related to or where COVID was the topic. One would think that sort of puts some limitations to or on the sort of hate speech involved. But who knows. Commenters might not be very rational so they might drag all sorts of things into it.
I can't really find, easily, what their own definition here is except in quite vague statements or groups (acceptable, inappropriate, offensive and violent). So they had four people annotate the comments and make judgements over in which group a comment should be tagged or belong.
In general this appears to be a problem in that they can't even agree upon what is hate speech or not. There might be the clear cases but then there is most likely a very large fuzzy thing in the middle. That doesn't even take into consideration that what is considered hate speech might very well change by context and over time as more and more things get included in the hate field. What was one acceptable can easily over time slide over into the inappropriate and offensive. If only someone gets offended by it.
So Youtube might already have deleted the really hateful things that broke their own codes of posting before the data reached the researchers. That could explain why they don't find any sign of the "pure haters".
By their third conclusion it seems that what they did find is that some users, of different opinions, like to troll each other by tossing gas on the fire.