The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …

In this paper, we review some advances made recently in the study of mobile phone
datasets. This area of research has emerged a decade ago, with the increasing availability …

Human mobility impacts many aspects of a city, from its spatial structure,–to its response to
an epidemic,,–. It is also ultimately key to social interactions, innovation, and productivity …

The study of socio-technical systems has been revolutionized by the unprecedented amount
of digital records that are constantly being produced by human activities such as accessing …

The breadcrumbs we leave behind when using our mobile phones—who somebody calls,
for how long, and from where—contain unprecedented insights about us and our societies …

Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic
status are significant for economic development. The understanding of socioeconomic …

Human mobility is a primary driver of infectious disease spread. However, existing data is
limited in availability, coverage, granularity, and timeliness. Data-driven forecasts of disease …

Dynamic human activity intensity information is of great importance in many location-based
applications. However, two limitations remain in the prediction of human activity intensity …

Human mobility is an important driver of geographic spread of infectious pathogens.
Detailed information about human movements during outbreaks are, however, difficult to …

Digital sources have been enabling unprecedented data-driven and large-scale
investigations across a wide range of domains, including demography, sociology …