In the wake of the terrorist attacks earlier this month on two mosques in Christchurch, New Zealand — which killed 50 people and injured 50 more — our partners at #WeCounterHate saw a surge in anti-Muslim tweets and activity.
#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 following the mass shootings:
• Anti-Muslim hate speech jumped nearly 8x in the three days following the shootings.
• Retweets of anti-Muslim hate speech jumped 91 percent.
• Likes of anti-Muslim hate speech jumped 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. Polarization is one step behind explicitly inciting violence against a target group.
• 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. But when a White Nationalist commits a violent attack, ALL White Nationalists are blamed.