Twitter Data Mining to Map Pedestrian Experience of Open Spaces

This research investigated the classification and visualisation of Twitter user-generated data. data were classified based on their sentiment relating to pedestrian experience quality open spaces, content. The methodology for collection, processing analysis included five phases: pre-processing, classification, analysis. territorial focus was Oxford Street, London, UK. Special attention placed questions regarding potential using extracting relevant topics public space investigating whether these can relate urban design improvement space. proposed model considered amount relevance, its possibilities interpretation collected sample, purpose quality, precision determination usability in relation a particular