LAUSR

A public space is a daily life environment for peoples’ social, cultural and recreational activities. Understanding people’s use and experience of urban public space is essential to create a better ground to design and improve the everyday spaces of people. Conventional methods for post-occupancy evaluation, like surveys, have common limitations: high-cost, time-consuming and non-real time interactions. Can social media data provide real-time and valuable insights about public space uses more effectively and promptly? This data-driven qualitative study explores the potential use of social media data for public space evaluation, focusing on the utilization of user-generated contents from social media as the source of user feedbacks. The High Line in New York City was selected as a case, and its related 9974 tweets were collected from Twitter over 14 months (August 2014–Oct 2015). The Twitter data were pre-processed through text-mining techniques and, for analysis, advanced computational techniques in social media analytics were performed. The research findings help us identify opportunities and challenges of using social media data analytics that can be adapted for research and practice in urban design, as part of public space evaluation in particular.