Leadership Instincts: Government launches an Empowered Group chaired by CEO NITI Aayog  |  Teacher Insights: KV Sangathan takes various steps for Online Teaching-Learning Process  |  Education Information: Not Sure of Reliability of News? Get It Verified at Covid19 Fact Check Unit  |  Science Innovations: Covid-19: DST funded startup develops chemical free silver based disinfectant   |  Technology Inceptions: A cost-effective virucidal coating of surgical masks from IIT Kanpur  |  Leadership Instincts: CSIR-IMTECH takes up sample testing for Covid-19  |  Creative Living: Music Industry Turns to Social Media To Bring Solace in Times of Pandemic  |  National Edu News: Hack the Crisis, Online Hackathon for Covid 19 Solutions  |  National Edu News: HRD Minister launches MHRD AICTE COVID-19 Student Helpline Portal   |  Science Innovations: University of Pittsburgh Covid-19 Vaccine Undergoes Animal Trials Successfully  |  Teacher Insights: UNICEF launches #ReadtheWorld initiative for children   |  Science Innovations: Covid-19 -Tracing the Route Map of the Clever Spiky Protein  |  Teacher Insights: Dr Christine Yao announced as BBC New Generation Thinker  |  International Edu News: New research on COVID-19's impact on youth mental health   |  Teacher Insights: Cambridge researchers awarded European Research Council funding  |  
August 03, 2017 Thursday 12:22:49 PM IST

Twitter can help in forecasting crime: Study

Technology Inceptions

New York: Microblogging site Twitter, which is open and accessible to anyone, can be used to help predict people engaged in criminal activity, a study has found.

Although "people don't share with the world that they intend to or have just committed a crime...(but) they do share are things like social events or outings that could lead to criminal activity", said Matthew Gerber, Assistant Professor at the University of Virginia in the US. 

For the study, presented at the Joint Statistical Meetings in Baltimore, the team developed statistical crime prediction methods which involved collecting more than 1.5 million public tweets tagged with Chicago-area GPS coordinates spanning January to March of 2013 as well as crime records covering the same period and geographic area. 

After dividing and mapping out tweets and crime records onto a grid and identifying common topics of discussion (e.g., sports, restaurants, and entertainment) appearing in tweets, Gerber combined conclusions from this analysis with older forecasting models to predict crimes over the next month. 


The result of his combined method was more precise, accurately predicting 19 out of 25 crime types. "Some cities that utilise such methods as a basis for resource allocation have seen dramatic decreases in crime," Gerber said. The research could assist police departments in resource allocation, deciding where and when to deploy officers.

Comments