Detection of barriers to mobility in the smart city using Twitter Articles uri icon

publication date

  • September 2020

start page

  • 168429

end page

  • 168438

volume

  • 8

International Standard Serial Number (ISSN)

  • 2169-3536

abstract

  • We present a system that analyzes data extracted from the microbloging site Twitter to detect the occurrence of events and obstacles that can affect pedestrian mobility, with a special focus on people with impaired mobility. First, the system extracts tweets that match certain prede ned terms. Then, it obtains location information from them by using the location provided by Twitter when available, as well as searching the text of the tweet for locations. Finally, it applies natural language processing techniques to con rm that an actual event that affects mobility is reported and extract its properties (which urban element is affected and how). We also present some empirical results that validate the feasibility of our approach.

keywords

  • mobility barriers; smartcity; social sensing; transport; twitter