SoylentNews is people
SoylentNews
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.
Source:
(Score: 5, Informative) by AthanasiusKircher on Monday February 13 2017, @06:59AM
Then the paragraph right below says anonymous comments account for 43%. Huge editorial fail or innumerancy? The rest of the paragraph makes as little sense so I'm leaning toward both.
The 43% clearly refers to the percentage of anonymous USERS compared to registered USERS in the table. (Here anonymous users are associated with an IP address.) The actual study (which I linked to in my post) makes this incredibly clear: "Table 4 shows that, last year, 43% of editing accounts were anonymous and these contributed 9.6% of the comments in our dataset."
The failure here, yet again, is not linking to the original study. Can I yet again make a strong request to editors (and submitters) to take 2 minutes to put in a link to an original research article when available? Here, the original study is even linked at the bottom of the article, so you don't even have to go searching for it. It's much clearer than the word salad of the article actually quoted in the summary. (Though again, I note the original article has problems too...)
(Score: 1) by charon on Tuesday February 14 2017, @03:07AM