Planning for Urban Satisfaction

Abstract

This paper aims to examine the strengths and weaknesses of social media platforms and proposes a vision for a better platform to invite bottom-up citizen participation in data-driven urban planning for urban satisfaction. The research proposes a method to measure the emotional response of individual citizens to the characteristics of the built environment focusing on proximity and convenience between pedestrians and nearby commercial and cultural activities. My proposed method requires a geotagged dataset with some measure of individual satisfaction with the built environment. The research demonstrates this method using Weibo posts tagged "Jiaxing", a small-sized city in China, coupled with a measure of each post's positivity, as estimated by the Baidu AI platform. The results illustrate that the combination of social media data and sentiment analysis is insufficiently specific to usefully inform planning decisions. I conclude with the proposal of a social media platform that could better measure individual satisfaction with the built environment.