{Reference Type}: Journal Article
{Title}: On an Aggregated Estimate for Human Mobility Regularities through Movement Trends and Population Density.
{Author}: Vanni F;Lambert D;
{Journal}: Entropy (Basel)
{Volume}: 26
{Issue}: 5
{Year}: 2024 Apr 30
{Factor}: 2.738
{DOI}: 10.3390/e26050398
{Abstract}: This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic.