Work

Human Mobility from theory to practice:Data, Models and Applications

Year: 2019

Type: conference-paper

Abstract: The inclusion of tracking technologies in personal devices opened the doors to the analysis of large sets of mobility data like GPS traces and call detail records. This tutorial presents an overview of both modeling principles of human mobility and machine learning models applicable to specific problems. We review the state of the art of five main aspects in human mobility: (1) human mobility data landscape; (2) key measures of individual and collective mobility; (3) generative models at the level of individual, population and mixture of the two; (4) next location prediction algorithms; (5) applications for social good. For each aspect, we show experiments and simulations using the Python library ”scikit-mobility” developed by the presenters of the tutorial.

Source: International World Wide Web Conference (WWW)

DOI: 10.1145/3308560.3320099

Authors: Luca Pappalardo, Gianni Barlacchi, Roberto Pellungrini, Filippo Simini

Institutions: Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo", University of Trento, University of Pisa, University of Bristol

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: hybrid

Funder: Engineering and Physical Sciences Research Council