Algorithm 90% accurate at spotting cyberbullies

A new algorithm can identify Twitter accounts carrying out bullying and troll-like behaviour with 90% accuracy, researchers have said.

The machine-learning software uses natural language processing and sentiment analysis on tweets to classify them as cyberbullying or cyberaggression.

The algorithm has been developed by researchers at Binghamton University in the United States.

The research comes as a number of high-profile personalities in the UK – including Gary Lineker and Rachel Riley – backed a new campaign to ignore and report abusive messages to help cut the spread of hate on social media. The researchers said their software had successfully identified bullying and aggressive accounts on Twitter with 90% accuracy.

Jeremy Blackburn, a computer scientist on the research team, said the new algorithm used information from Twitter profiles as well as looking for connections between accounts.

Social media platforms have come under increased pressure to do more to protect their users from hateful and harmful content after a number of concerns were raised around the impact of such sites on mental health and wellbeing, particularly among young people.