Researchers at Binghamton University say that a new algorithm which can classify two specific types of offensive online behaviour such as cyber-bullying and cyber-aggression can identify Twitter accounts engaging in bullying with over 90% accuracy.
According to a report by BBC, Jeremy Blackburn, a computer scientist on the research team, said the algorithms looked for connections between offensive accounts by using information from Twitter profiles.
Blackburn said: “We built crawlers – programs that collect data from Twitter via a variety of mechanisms.”
“We gathered tweets of Twitter users, their profiles, as well as [social-]network-related things, like who they follow and who follows them. In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” he added.
Meanwhile, Twitter earlier assured users about keeping their service healthy as it stated: “Our priority is ensuring our service is healthy, and free of abuse or other types of content that can make others afraid to speak up, or put themselves in vulnerable situations.”
According to charity Ditch the Label, one in three teenagers living in fear of online abuse, making cyber-bullying as a widespread issue.
(Photo source: techcrunch.com/ time.com)