Related papers: Human Mobility and Predictability enriched by Soci…
Understanding fashion styles and trends is of great potential interest to retailers and consumers alike. The photos people upload to social media are a historical and public data source of how people dress across the world and at different…
Human mobility forms the backbone of contact patterns through which infectious diseases propagate, fundamentally shaping the spatio-temporal dynamics of epidemics and pandemics. While traditional models are often based on the assumption…
This chapter examines the possibility to analyze and compare human activities in an urban environment based on the detection of mobile phone usage patterns. Thanks to an unprecedented collection of counter data recording the number of…
Human mobility is one of the key factors at the basis of the spreading of diseases in a population. Containment strategies are usually devised on movement scenarios based on coarse-grained assumptions. Mobility phone data provide a unique…
Since users move around based on social relationships and interests, the resulting movement patterns can represent how nodes are socially connected (i.e., nodes with strong social ties, nodes that meet occasionally by sharing the same…
The identification of urban mobility patterns is very important for predicting and controlling spatial events. In this study, we analyzed millions of geographical check-ins crawled from a leading Chinese location-based social networking…
The rise of location positioning technologies has generated enormous volumes of digital footprints. Translating this big data into understandable trip patterns plays a crucial role in estimating infrastructure demands. Previous studies were…
High quality census data are not always available in developing countries. Instead, mobile phone data are becoming a trending proxy to evaluate population density, activity and social characteristics. They offer additional advantages for…
Mobile phone use is an unfolding process by nature. In this study, it is explicated as two sequential processes: mobile sessions composed of an uninterrupted set of behaviors and mobile trajectories composed of mobile sessions and…
In this article, we present a distributed framework for collecting and analyzing environmental and location data recorded by human users (carriers) with the use of portable sensors. We demonstrate the data mining analysis potential among…
While a social event, such as a concert or a food festival, is a common experience to people, a natural disaster is experienced by a fewer individuals. The ordinary and common ground experience of social events could be therefore used to…
Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural…
Every day, billions of mobile network events (i.e. CDRs) are generated by cellular phone operator companies. Latent in this data are inspiring insights about human actions and behaviors, the discovery of which is important because…
Physical contacts result in the spread of various phenomena such as viruses, gossips, ideas, packages and marketing pamphlets across a population. The spread depends on how people move and co-locate with each other, or their mobility…
Statistics on migration flows are often derived from census data, which suffer from intrinsic limitations, including costs and infrequent sampling. When censuses are used, there is typically a time gap - up to a few years - between the data…
Rapid urbanization and climate change trends are intertwined with complex interactions of various social, economic, and political factors. The increased trends of disaster risks have recently caused numerous events, ranging from…
In this paper, we propose a general analytical framework for information spreading in mobile networks based on a new performance metric, mobile conductance, which allows us to separate the details of mobility models from the study of mobile…
We apply a simple clustering algorithm to a large dataset of cellular telecommunication records, reducing the complexity of mobile phone users' full trajectories and allowing for simple statistics to characterize their properties. For the…
Population mobility can be studied readily and cheaply using cellphone data, since people's mobility can be approximately mapped into tower-mobile registries. We model people moving in a grid-like city, where edges of the grid are weighted…
Human mobility describes physical patterns of movement of people within a spatial system. Many of these patterns, including daily commuting, are cyclic and quantifiable. These patterns capture physical phenomena tied to processes studied in…