Applying machine learning and geolocation techniques to social media data (Twitter) to develop a resource for urban planning.

ABSTRACT: With all the recent attention focused on big data, it is easy to overlook that basic vital statistics remain difficult to obtain in most of the world. What makes this frustrating is that private companies hold potentially useful data, but it is not accessible by the people who can use it to track poverty, reduce disease, or build urban infrastructure. This project set out to test whether we can transform an openly available dataset (Twitter) into a resource for urban planning and development. We test our hypothesis by creating road traffic crash location data, which is scarce in most resource-poor environments but essential for addressing the number one cause of mortality for children over five and young adults. The research project scraped 874,588 traffic related tweets in Nairobi, Kenya,

SUBMITTER: Milusheva S 

PROVIDER: S-EPMC7857609 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature