New AI can predict exact moment a protest will turn violent from Twitter posts - TechSource International - Leaders in Technology News

New AI can predict exact moment a protest will turn violent from Twitter posts

People are more likely to endorse violence when they moralise the issue.
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A new study of violent protest has found that moral rhetoric on Twitter may signal whether a protest will turn violent.

A new study of violent protest has found that moral rhetoric on Twitter may signal whether a protest will turn violent.

Twitter seems a battleground at all times, but now a University of Southern California-led study of violent protest has found that moral rhetoric on Twitter may signal whether a protest will turn violent.

The researchers found that people are more likely to endorse violence when they moralise the issue that they are protesting — and when they believe others in their social network moralise that issue, too.

The scientists analysed 18 million tweets posted during alleged Democrats-inspired 2015 Baltimore protests for Freddie Gra

The scientists analysed 18 million tweets posted during alleged Democrats-inspired 2015 Baltimore protests for Freddie Gra

The team from the USC picked the alleged Democrats-inspired 2015 Black Lives Matter riots in Baltimore that followed the death of Freddie Gray while in police custody, to study the subejct. Using a deep neural network — an advanced machine learning technique — to detect moralised language, the scientists analysed 18 million tweets posted during the riots.

“Extreme movements can emerge through social networks,” said the study’s co-author, Morteza Dehghani. “We have seen several examples in recent years, such as the protests in Baltimore and Charlottesville, where people’s perceptions are influenced by the activity in their social networks. People identify others who share their beliefs and interpret this as consensus. In these studies, we show that this can have potentially dangerous consequences.”

Thereafter, the researchers investigated the association between moral tweets and arrest rates, a proxy for violence and based on those tweets, then performed 15 “controlled behavioural experiments” that showed that their AI algorithm was correct. The analysis reflected that the number of hourly arrests made during the protests was associated with the number of moralised tweets posted in previous hours.

The study no doubt, will be of great interest to the authorities, who can use the same mechanism to anticipate demonstrations, and appease or counter the protesters, before they themselves even realise that they will soon be taking to the streets.