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Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences…

计算机与社会 · 计算机科学 2013-01-29 Thomas Couronne , Zbigniew Smoreda , Ana-Maria Olteanu

Human mobility has been traditionally studied using surveys that deliver snapshots of population displacement patterns. The growing accessibility to ICT information from portable digital media has recently opened the possibility of…

Circadian rhythms are known to be important drivers of human activity and the recent availability of electronic records of human behaviour has provided fine-grained data of temporal patterns of activity on a large scale. Further,…

Humans follow circadian rhythms, visible in their activity levels as well as physiological and psychological factors. Such rhythms are also visible in electronic communication records, where the aggregated activity levels of e.g. mobile…

A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire…

社会与信息网络 · 计算机科学 2018-01-25 Anders Mollgaard , Sune Lehmann , Joachim Mathiesen

Home-work commuting has always attracted significant research attention because of its impact on human mobility. One of the key assumptions in this domain of study is the universal uniformity of commute times. However, a true comparison of…

社会与信息网络 · 计算机科学 2015-06-17 Kevin S. Kung , Kael Greco , Stanislav Sobolevsky , Carlo Ratti

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…

物理与社会 · 物理学 2018-02-07 Daniel Monsivais , Asim Ghosh , Kunal Bhattacharya , Robin I. M Dunbar , Kimmo Kaski

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…

社会与信息网络 · 计算机科学 2019-08-08 Mikaela Irene D. Fudolig , Daniel Monsivais , Kunal Bhattacharya , Hang-Hyun Jo , Kimmo Kaski

We study the influence of seasonally and geographically related daily dynamics of daylight and ambient temperature on human resting or sleeping patterns using mobile phone data of a large number of individuals. We observe two daily…

物理与社会 · 物理学 2017-04-21 Daniel Monsivais , Kunal Bhattacharya , Asim Ghosh , Robin I. M. Dunbar , Kimmo Kaski

The enormous amount of recently available mobile phone data is providing unprecedented direct measurements of human behavior. Early recognition and prediction of behavioral patterns are of great importance in many societal applications like…

社会与信息网络 · 计算机科学 2015-10-13 Zolzaya Dashdorj , Stanislav Sobolevsky

Understanding human mobility is essential for many fields, including transportation planning. Currently, surveys are the primary source for such analysis. However, in the recent past, many researchers have focused on Call Detail Records…

机器学习 · 计算机科学 2021-08-23 Buddhi Ayesha , Bhagya Jeewanthi , Charith Chitraranjan , Amal Shehan Perera , Amal S. Kumarage

Transportation provides access to employment opportunities and essential services such as healthcare services; while urban areas have various transportation options, the situation differs in rural areas. Rural residents often have longer…

The massive amounts of geolocation data collected from mobile phone records has sparked an ongoing effort to understand and predict the mobility patterns of human beings. In this work, we study the extent to which social phenomena are…

物理与社会 · 物理学 2016-11-18 Nicolas Ponieman , Alejo Salles , Carlos Sarraute

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected…

物理与社会 · 物理学 2015-08-06 Jari Saramaki , Esteban Moro

Using large-scale call detail records of anonymised mobile phone service subscribers with demographic and location information, we investigate how a long-distance residential move within the country affects the mobile communication patterns…

社会与信息网络 · 计算机科学 2021-04-07 Mikaela Irene D. Fudolig , Daniel Monsivais , Kunal Bhattacharya , Hang-Hyun Jo , Kimmo Kaski

Mobile phone data have played a key role in quantifying human mobility during the COVID-19 pandemic. Existing studies on mobility patterns have primarily focused on regional aggregates in high-income countries, obfuscating the accentuated…

We present a link-centric approach to study variation in the mobile phone communication patterns of individuals. Unlike most previous research on call detail records that focused on the variation of phone usage across individual users, we…

社会与信息网络 · 计算机科学 2020-01-08 Mikaela Irene D. Fudolig , Kunal Bhattacharya , Daniel Monsivais , Hang-Hyun Jo , Kimmo Kaski

The information collected by mobile phone operators can be considered as the most detailed information on human mobility across a large part of the population. The study of the dynamics of human mobility using the collected geolocations of…

社会与信息网络 · 计算机科学 2013-11-21 Nicolas Ponieman , Alejo Salles , Carlos Sarraute

Despite their importance for urban planning, traffic forecasting, and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited thanks to the lack of tools to monitor the time…

物理与社会 · 物理学 2009-11-13 M. C. Gonzalez , C. A. Hidalgo , A. -L. Barabasi

Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel between locations: by direct observations…

物理与社会 · 物理学 2014-08-25 Vasyl Palchykov , Marija Mitrović , Hang-Hyun Jo , Jari Saramäki , Raj Kumar Pan
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