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A joint study carried out 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, one of the many faces of online abuse. To analyze the gigantic trove of sample comments, researchers developed a machine learning algorithm that was able to identify and distinguish different forms of online abuse and personal attacks. In order for the algorithm to work, it had to be trained beforehand. For this, researchers used human users to classify a small batch of 100,000 comments, with each of the test comments passing through the hands of ten different humans. The resulted data classification allowed the algorithm to accurately distinguish between direct personal attacks (statements like "You suck!"), third-party personal attacks (statements like "Bob sucks!"), and indirect personal attacks (statements like "Henry said Bob sucks").
After training the algorithm and unleashing it on all Wikipedia 2015 user comments, researchers were able to identify personal attacks, and then collect data on the users that launched them. Their findings reveal that around 43% of all comments left on Wikipedia came from anonymous users, but most of these were one-time commenters, and the number of comments they left was 20 times smaller than comments left by registered users. Despite this, researchers discovered that anonymous users were six times more active in posting personal attacks, but in the end, they contributed to less than half of personal attacks, meaning a large number of personal attacks came from users with a registered identity on the site.
Of all personal attacks, researchers noted that about a tenth came from extremely active users, who had an activity level of 20+, the highest on the site. A closer look at the data revealed that 34 "highly toxic users" from this 20+ category were responsible for almost 9% of all personal attacks on the site. "By comparing these figures, we see that almost 80% of attacks come from the over 9000 users who have made fewer than 5 attacking comments," the research team noted, something that's somewhat normal, as everybody tends to get mad at one point or another. "However, the 34 users with a toxicity level of more than 20 are responsible for almost 9% of attacks," researchers noted.
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(Score: 2) by zocalo on Monday February 13 2017, @10:13AM
There isn't really anything new in this other than identifying names and numbers specific to Wikipedia though; many forums have a handful of toxic users that prompt this kind of response, including other "supporting" comments that spiral out of control. It is worth bearing in mind though that sometimes the cause is not someone out to deliberately troll/inflame, but actually slightly more benign; the language barrier. Not everyone is a native speaker of English and without a good grasp of both spoken and written English, including the use of idioms, it's not at all uncommon to come across someone who unintentionally comes off as slightly - or exceedingly - abrasive when using a secondary language.
UNIX? They're not even circumcised! Savages!
(Score: 2) by VLM on Monday February 13 2017, @02:13PM
The result would be a McDonalds hamburger of merely 91% protein of unknown animal source rather than 100%, it would feel good yet accomplish very little. Even if intimidation took hold it would still be twice of about nothing is still nothing.
There are other side issues of course where I suspect I know the politics of those involved and the last thing we need is a Hollywood actor's crusade and a fake news barrage of clickbait in response to action. Its entirely possible due to secondary effects that the situation could deteriorate rather than improve.