Image credit: Jason Howie / CC BY 2.0Researchers from Cardiff University believe that police officers using social media may improve response times to both large- and small-scale disruptive events.
Using a series of machine learning algorithms to analyze data such as tweets associated with the 2011 London riots, researchers found in almost all scenarios that the algorithms were able to detect disruptive events (cars set on fire and stores being broken into) before they were reported to the police — sometimes up to an hour before the events were reported.
Co-author of the study, Dr. Pete Burnap from Cardiff University's School of Computer Science and Informatics, said: "We have previously used machine-learning and natural language processing on Twitter data to better understand online deviance, such as the spread of antagonistic narratives and cyber hate.”
"In this research we show that online social media are becoming the go-to place to report observations of everyday occurrences — including social disorder and terrestrial criminal activity. We will never replace traditional policing resource on the ground but we have demonstrated that this research could augment existing intelligence gathering and draw on new technologies to support more established policing methods."
As part of their ongoing research, scientists continue to scan through Twitter, YouTube, and Facebook to detect incidents in real-time.
Dr. Nasser Alsaedi, who recently completed his PhD at Cardiff under the supervision of Dr. Burnap, said: "Coming from a policing background myself I see the need for this type of cutting edge research every day. I wanted to develop a thesis that could have a real impact in real-world policing. I would like to see this implemented alongside the established decision-making processes."
The study is published in the journal ACM Transactions on Internet Technology.
