Trip distribution modeling with Twitter data

Nastaran Pourebrahim, Selima Sultana, Amirreza Niakanlahiji, Jean-Claude Thill

Abstract: Highlights•Traditional and social media data are integrated to predict commuting trip distribution.•The predictive performance of the traditional gravity model and ML techniques is evaluated.•The potential of Twitter data in trip distribution modeling at fine spatial scale is explored.•The most significant predictor variables are determined.