New algorithm to identify cyber-bullies on Twitter

Researchers have developed machine learning algorithms which can identify bullies and aggressors on Twitter with 90 per cent accuracy.

A research based study published in the journal Transactions on the Web analysed the behavioural patterns exhibited by abusive Twitter users and their differences from other users.

"We built crawlers programs that collect data from Twitter via variety of mechanisms," said study researcher Jeremy Blackburn from Binghamton University in the US.

"We gathered tweets of Twitter users, their profiles, as well as (social) network-related things, like who they follow and who follows them," Blackburn said.

The researchers then performed natural language processing and sentiment analysis on the tweets themselves, as well as a variety of social network analyses on the connections between users.

They developed algorithms to automatically identify two specific types of inappropriate online behaviour, i.e. cyber-bullying and cyber-aggression.

The algorithms were able to identify abusive users engaging in harassing behaviour patterns such as those sending death threats or making racist remarks with 90 per cent accuracy.

( With inputs from IANS )