A joint study by researchers from Alphabet’s Jigsaw and the Wikimedia Foundation has analyzed all user comments left on Wikipedia in 2015 in order to identify how and why users launch in personal attacks. A machine learning algorithm was able to identify and distinguish different forms of online abuse and personal attacks using a small batch of 100,000 comments. Anonymous users are 6 times more likely to launch personal attacks than registered users. A tenth of all personal attacks came from extremely active users with an activity level of 20+, the highest on the site.
Source: https://www.bleepingcomputer.com/news/security/wikipedia-comments-destroyed-by-a-few-highly-toxic-users/

