Tweets may help improve urban planning

Geo-localised tweets can be a very useful source of information for urban planning and land use, a new study has found.

Researchers have already done it in Manhattan, Madrid and London and have been able to identify, for example, nightlife areas of these large cities.

Every day millions of citizens around the world generate massive amounts of geolocalised content using mobile applications and social networks.

Especially on Twitter, which could become a sensor of interactions between people and their environment and provide guidelines for planning life in the city.

A forgotten issue in urbanism is land use during the night time, with problems such as noise and dirt, which could be improved with this type of tool.

Enrique and Vanessa Frias-Martinez, researchers at Telefonica Research in Madrid and the University of Maryland (US) respectively, have suggested using geolocalised tweets for urban planning and land use.

'Geolocalised tweets can be a very useful source of information for planning, since it is an activity carried out by a large number of people who provide information on where they are at a specific time and what they are doing,' Enrique said.

The researcher points out that 'thanks to the increased use of smartphones, social networks like Twitter and Facebook have made it possible to access and produce information ubiquitously.'

These networks, he added, generate tags with the event's geolocation.

highly suited to helping in urban planning, especially in identifying land use,' researchers said.

Using Twitter, 'you can capture information on urban land use more efficiently and for a much larger number of people than with questionnaires,' said Enrique.

The new technique 'automatically determines land uses in urban areas by grouping together geographical regions with similar patterns of Twitter activity,' researchers said.

Using aggregate activity of tweets, the researchers have studied land use in Manhattan, Madrid and London.

In the first two cases they identified four uses: residential, business, daytime leisure (mainly parks and tourist areas) and nightlife areas. In London, they also

The study was published in the journal Engineering Applications of Artificial Intelligence.