Twitter is filled with hatred and offensive posts. There’s no no doubt about it. The medium serves as an echo chamber — one that provides instant feedback — to those who want to outrage and vent their anger. It also breeds other undesirable phenomenona, such as bullying and racism.
How does one filter such messages? How do we identify violent groups that thrive in such a medium?
Researchers at the University of Salamanca (USAL) have developed sentiment analysis algorithms capable to monitor the social network Twitter and locate violent groups by analysing the messages they share.
“This system could have been very useful -for example- as a support system to control the violent football fans that caused serious incidents during Euro 2016 in France,” says Sinc Juan Manuel Corchado, professor of Computer Science and leader of the Bisite artificial intelligence team at USAL.
How does the system work?
The advantage of the new application, says Dr. Corchado, is that it can analyse emotions in different languages -at the moment, Spanish, English, French, German, Russian and Arabic-. Also, continuously extract communications information and see changes in individuals’ sentiments and physical location, analysing group interrelationships at the same time.
Depending on the traffic generated between people, it is possible to identify the members of a group, its leaders and followers. It is also possible to see how relationships evolve and whether new members join a group. In addition, says the researcher, having identified the leaders, the tool can try to influence them to change their sentiments.
It can also be used to analyse what’s being said about companies, brands and people on social media.
According to Dr. Corchado, the police and other law enforcement agencies could use the tool to detect critical points, threats and areas with concentrations of potentially dangerous people. “It’s based both on the semantic analysis of messages and historical data and their evolution.”