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New algorithm to identify cyber-bullies on Twitter

New York - "We built crawlers - programs that collect data from Twitter via variety of mechanisms," said study researcher Jeremy Blackburn.

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Researchers have developed machine learning algorithms which can identify bullies and aggressors on Twitter.
For the study published in the journal Transactions on the Web, the research team 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 classify two specific types of offensive online behaviour, i.e. cyber-bullying and cyber-aggression.
The algorithms were able to identify abusive users - who engage in harassing behaviour like those who send death threats or make racist remarks - on Twitter with 90 per cent accuracy.

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