A brother-sister team of Spanish researchers has found that geo-localized tweets can be a very useful source of information for urban planning and land use. Also Read - RIP Fleets! Twitter officially shuts disappearing tweets feature
Every day, millions of citizens around the world generate massive amounts of geolocalised content using mobile applications and social networks. Twitter especially can become a sensor of interactions between people and their environment and provide guidelines for planning life in the city. Enrique and Vanessa Frías-Martínez, computer science researchers at Madrid-based Telefonica Research and University of Maryland in the US, respectively, pointed 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”. Also Read - Twitter Bug Bounty Contest to offer $3500 cash prize for detecting algorithm bias
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. “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,” the duo noted. “For example, Twitter includes longitude-latitude information in the tweet if the user so desires. Among possible applications we have seen that this network could be highly suited to helping in urban planning, especially in identifying land use,” Enrique said. Also Read - COVID-19 third wave: Twitter shuts offices as coronavirus cases rise
Using Twitter, “you can capture information on urban land use more efficiently and for a much larger number of people than with questionnaires”, he said. The new technique automatically determines land uses in urban areas by grouping together geographical regions with similar patterns of Twitter activity, the researcher added.
Using aggregate activity of tweets, the siblings 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 established industrial land uses. These results were validated with open data sources. The findings were published in the journal Engineering Applications of Artificial Intelligence.