How data can identify accident black spots, improve transport and life in the city

University of Melbourne researchers – armed with the right analytical tool – are finding Twitter data surprisingly useful. They’re mining the data and looking for patterns, from identifying real-time traffic jams to measuring community sentiment to even finding the hotspots for bad language.

Social tools such as Twitter can provide a wealth of data for urban researchers. Picture: Pexels

“We have built a way to harvest Twitter data while people are on the roads. It’s a controversial idea, because people shouldn’t be tweeting while they’re driving,” says Professor Richard Sinnott, director of the Melbourne eResearch Group and from the Melbourne School of Engineering’s Department of Computing and Information Systems.

Professor Sinnott and his team do their analysis using Australia’s road system data, available through the Australian Research Infrastructure Portal (AURIN) portal.

“Just as measuring a person’s vital signs — pulse, temperature, breathing rate and blood pressure —tell you a lot about their health. Measuring signs of activity, life and movement in a city can tell you how functional or dysfunctional it is,” says Dr Serryn Eagleson, an urban researcher and Manager Data and Business Applications at AURIN.

Collectively the AURIN community have curated and integrated vast amounts of urban data — over 2,000 datasets from 40 providers — mapped it and developed tools to analyse it so that researchers like Richard can put it to use.

“We’ve written a set of algorithms that identify tweets that originate on the road system. You can write an algorithm that moves along CityLink or the West Gate Bridge in Melbourne, or the Southern Expressway south of Adelaide, checking for tweets in each small section of the road,” Professor Sinnott explains.

Originally Published by Tanya Ha, University of Melbourne read full article here.


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