Accessibility of touristic venues in Amsterdam: A methodology to collect, assess and validate the attractiveness and accessibility of touristic venues from data extracted using Twitter as Urban Sensor: A.M.S. case

Abstract

Amsterdam attracts every year a growing number of tourists which can generate congestion and overcrowding in the city centre. To tackle this problem, a state-of-art method that enables new ways of collecting large amount of spatio-temporal data to study how people use the urban environment is needed. The research is aimed at develop, implement and validate a method to extract tourism information from Twitter LBSN by using techniques of the Geographic Knowledge Discovery methodology in combination with Python programming and ArcMap platforms. With this method the author assess the attractiveness of touristic venues through the implementation of a gravity model thus finding where and when urban solutions to tackle congestion and overcrowding are needed the most.