A Machine Learning Application to Google Maps Reviews as A Participatory Planning Tool

Abstract

Public participation is vital to achieving successful plan outcomes, whereas meaningful participation requires at least informing and consulting the public. However, collecting frequent feedback from the public is a labor-intensive process. Information technologies like Google Maps Reviews offer to collect extensive public inputs by allowing users to share their feedback and ratings about services. Machine learning methods are ideal for analyzing these reviews to under-stand users’ experiences. This study proposes a machine learning application to examine feedback on the selected parks in Istanbul, Turkey using Google Maps Reviews. The introduced method supports surveys and interview methods preferred by planners.

Keywords: public participation, user experience, XGBoost, Shapley value, Istanbul