This seems likely to you?
This seems likely to you?
Reminds me of old Twitter again.
[0]https://journals.sagepub.com/doi/10.1177/0956797615576473
Find me the news channel watched by 60 million people that is willing to say the same thing about Christians.
I’d be actually shocked to find out the reverse. A good percentage of the US were born up in an era where you could legally bar people based on their race from your establishment. The extremely heated fight over gay marriage is still fresh in people’s memory. Trans rights are a controversial political issue where many mainstream politicians want to legislate them out of public spaces, because of public sentiment. And for the left/right leaning question, In the last two major elections we’ve seen the political discourse even of republicans politicians and leaders is comparatively charged with violence.
The hate is definitely there against the republicans and mainstream groups, but I would expect it to be relatively uncommon compared to the hateful text you can find online about other groups. This could be a real problem for novel kinds of hate speech.
However, it’s also true that I can trivially find clips of mainstream republican leaders over the last few years with violent charged rhetoric, and it is comparatively harder to find such rhetoric from mainstream democrats[0][1]
For many of the other groups, hate has been historically so widespread and common there are whole organizations like the annti defamation league organized around combating it. There is no way that even if you believe today people are furiously writing hate against Christians into twitter 24/7 or wherever my bubble they could have caught up with the historic use of hate speech against Muslims in the wake of 9/11. And so on for the other disadvantaged groups.
And all this is not to say it isn’t a potential problem or a potentially useful metric. It could be that synthetic hate is needed to anticipate new kinds of unlikely and rare sentence structures that might arise. If this is true it also reminds us that these models will need constant training as new kinds of hate speech become more popular and that it will always be lagging.
[0]https://apnews.com/article/donald-trump-fred-upton-paul-gosa...
[1[https://www.pbs.org/newshour/amp/show/how-some-members-of-th...
And that’s what this metric is measuring, the model finding hate more easily with “fat people are terrible” than “normal weight people are terrible”
Hateful expression is more prominent when it’s socially acceptable, and in American society at large, there are socially acceptable targets for hate that do not align with the majority/minority group division.
Consider, for example, the prominent, public, long-standing (and for some reason, tolerated) racial animosity between Asian and Black Americans.
You say you don't know why it's tolerated, but that's my point exactly; it's tolerated because it's hate towards a minority group (regardless of the source). It would be substantially less tolerated if it were hate towards the majority group.
Consider how often you’ve read “kill all men” or “kill all terfs”, versus “kill all women” or “kill all transgender people”.
Furthermore, consider the stronger emotional reaction you likely had to reading the second two, as opposed to the first two.
By contrast, trans-identifying people are comparatively celebrated in our society.