  Walkability has many health, environmental, and economic benefits. That is
why web and mobile services have been offering ways of computing walkability
scores of individual street segments. Those scores are generally computed from
survey data and manual counting (of even trees). However, that is costly, owing
to the high time, effort, and financial costs. To partly automate the
computation of those scores, we explore the possibility of using the social
media data of Flickr and Foursquare to automatically identify safe and walkable
streets. We find that unsafe streets tend to be photographed during the day,
while walkable streets are tagged with walkability-related keywords. These
results open up practical opportunities (for, e.g., room booking services,
urban route recommenders, and real-estate sites) and have theoretical
implications for researchers who might resort to the use social media data to
tackle previously unanswered questions in the area of walkability.
