#WeCounterHate combats hate speech on Twitter using artificial intelligence to tag, and track, tweets that use dehumanizing language to attack people. Here’s what we found in the tweets the AI reviewed:
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In the wake of last week’s terrorist attacks on two mosques in Christchuch, NZ, our partners at @WeCounterHate saw a surge in anti-Muslim tweets and RTs. (a thread ...)
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• Anti-Muslim hate speech increased 8x in the three days following the shootings. • Retweets of anti-Muslim hate speech jumped 91 percent.
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• Likes of anti-Muslim hate speech increased by more than 125 percent. • There was a 62 percent increase in language that evokes “polarization,” which is the second highest-intensity form of hate speech on our scale. That’s one step behind explicitly calling for violence.
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• There was also a 32 percent increase in “classification language.” In this case, white nationalists lamented a perceived double standard. Their claim: When a Muslim commits a violent attack, they (white nationalists) aren’t allowed to blame ALL Muslims.
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But when a white nationalist commits a violent attack, ALL white nationalists are blamed. Example:pic.twitter.com/vbx3BZ655N
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There’s this idea that white nationalism is a peaceful ideology (it isn’t).
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@WeCounterHate and support however you can. Last year, it reduced the spread of hate speech by more than 9 million impressions. 9 MILLION!!!!Afficher cette discussion
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