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Cities are inherently dynamic. Interesting patterns of behavior typically manifest at several key areas of a city over multiple temporal resolutions. Studying these patterns can greatly help a variety of experts ranging from city planners…
In this paper we predict outgoing mobile phone calls using a machine learning approach. We analyze to which extent the activity of mobile phone users is predictable. The premise is that mobile phone users exhibit temporal regularity in…
The massive digital footprints generated by bike-sharing systems in megacities like Shanghai offer a novel perspective on the urban socio-economic fabric. This study investigates whether these daily mobility patterns can quantitatively map…
Mobility is a fundamental feature of human life, and through it our interactions with the world and people around us generate complex and consequential social phenomena. Social segregation, one such process, is increasingly acknowledged as…
Novel aspects of human dynamics and social interactions are investigated by means of mobile phone data. Using extensive phone records resolved in both time and space, we study the mean collective behavior at large scales and focus on the…
In transport modeling and prediction, trip purposes play an important role since mobility choices (e.g. modes, routes, departure times) are made in order to carry out specific activities. Activity based models, which have been gaining…
We analyze a large-scale mobile phone call dataset containing information on the age, gender, and billing locality of users to get insight into social closeness in pairs of individuals of similar age. We show that in addition to using the…
Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously…
There are different functional regions in cities such as tourist attractions, shopping centers, workplaces and residential places. The human mobility patterns for different functional regions are different, e.g., people usually go to work…
As computing technology becomes more pervasive, personal devices such as the PDA, cell-phone, and notebook should use context to determine how to act. Location is one form of context that can be used in many ways. We present a…
Studies show that psychological effects are among one of the top concerns for public transportation users. While many Americans spend a significant portion of their time in public transportation spaces, the impact of the design and…
Context information brings new opportunities for efficient and effective applications and services on mobile devices. A wide range of research has exploited context dependency, i.e., the relations between context(s) and the outcome, to…
Shared e-scooters have become a familiar sight in many cities around the world. Yet the role they play in the mobility space is still poorly understood. This paper presents a study of the use of Bird e-scooters in the city of Atlanta.…
Previous studies have shown that Twitter users have biases to tweet from certain locations, locational bias, and during certain hours, temporal bias. We used three years of geolocated Twitter Data to quantify these biases and test our…
Data on human spatial distribution and movement is essential for understanding and analyzing social systems. However existing sources for this data are lacking in various ways; difficult to access, biased, have poor geographical or temporal…
Tourists tend to visit multiple destinations out of their variety-seeking motivations in their trips. Thus, it is critical to discover travel patterns involving multi-destinations in tourism research. Existing relevant research most relied…
The ubiquity and on-the-go availability of mobile devices makes them central to many tasks such as interpersonal communication and media consumption. However, despite the potential of mobile devices for on-demand exploratory data…
Nowadays as the world population has become more interconnected and is relying on faster transportation methods, simplified connections and shorter commuting times, we witness a rapid increase in human mobility. In this situation unveiling…
Properly extracting patterns of individual mobility with high resolution data sources such as the one extracted from smartphone applications offers important opportunities. Potential opportunities not offered by call detailed records…
The recent development of smartphone and wearable sensor technologies enable general public to carry self-tracking tasks more easily. Much work has been devoted to life data collection and visualisation to help people with better…