Analyzing urban vitality patterns with topological data analysis
Krasen Samardzhiev and Daniel Arribas-Bel
Urban researchers have found various uses for new forms of data such as twitter data and mobile phone data, by adapting old methods or adopting new ones from fields such as machine learning. Topological data analysis is a promising new data analysis paradigm, that tries to quantify the qualitative properties of the data, such as its shape. This paper uses these new methods to quantitatively analyze and group areas that exhibit similar patterns of urban vitality within the province of Milan.