How average is average? Temporal patterns in human behaviour as measured by mobile phone data -- or why chose Thursdays
@article{Toger2020HowAI, title={How average is average? Temporal patterns in human behaviour as measured by mobile phone data -- or why chose Thursdays}, author={Marina Toger and Ian G. Shuttleworth and John Osth}, journal={arXiv: General Economics}, year={2020} }
Mobile phone data -- with file sizes scaling into terabytes -- easily overwhelm the computational capacity available to some researchers. Moreover, for ethical reasons, data access is often granted only to particular subsets, restricting analyses to cover single days, weeks, or geographical areas. Consequently, it is frequently impossible to set a particular analysis or event in its context and know how typical it is, compared to other days, weeks or months. This is important for academic…
3 Citations
Mobility during the COVID-19 Pandemic: A Data-Driven Time-Geographic Analysis of Health-Induced Mobility Changes
- EconomicsSustainability
- 2021
The COVID-19 pandemic has profoundly affected the spatial mobility of a major part of the population in many countries. For most people, this was an extremely disruptive shock, resulting in loss of…
Daily Mobility Patterns: Reducing or Reproducing Inequalities and Segregation?
- Economics
- 2021
Theory states that residential segregation may have a strong impact on people’s life opportunities. It is unclear, however, to what extent the residential environment is a good representation of…
Segregation and the pandemic: The dynamics of daytime social diversity during COVID-19 in Greater Stockholm
- SociologyApplied Geography
- 2023
References
SHOWING 1-10 OF 19 REFERENCES
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore
- Computer ScienceIEEE Transactions on Big Data
- 2017
This research provides an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes.
Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data
- Environmental SciencePloS one
- 2016
This work contributes to a deeper understanding of regularities in patterns of transit use from variations in volumes of travellers entering subway stations, establishes a generic analytical framework for comparative studies using urban mobility data, and provides key points for the management of variability by policy-makers intent on for making the travel experience more amenable.
Spatial and temporal patterns of economic segregation in Sweden’s metropolitan areas: A mobility approach
- Economics
- 2018
The statistical resources at hand for segregation research are usually almost exclusively confined to annual or decennial records where the only available spatial information is the individual’s…
Mobile phone data and COVID-19: Missing an opportunity?
- Political ScienceArXiv
- 2020
This paper describes how mobile phone data can guide government and public health authorities in determining the best course of action to control the COVID-19 pandemic and in assessing the…
How to Draw a Neighborhood? The Potential of Big Data, Regionalization, and Community Detection for Understanding the Heterogeneous Nature of Urban Neighborhoods
- Sociology
- 2018
How to draw neighborhood boundaries, or spatial regions in general, has been a long-standing focus in Geography. This article examines this question from a methodological perspective, often referred…
Mobility, Data Mining and Privacy - Geographic Knowledge Discovery
- Computer ScienceMobility, Data Mining and Privacy
- 2008
This book tightly integrates and relates their findings in 13 chapters covering all related subjects, including the concepts of movement data and knowledge discovery from movement data; privacy-aware geographic knowledge discovery; wireless network and next-generation mobile technologies; trajectory data models, systems and warehouses; privacy and security aspects of technologies and related regulations.
Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing.
- MedicineJAMA
- 2020
Taiwan is an example of how a society can respond quickly to a crisis and protect the interests of its citizens in the face of an emerging epidemic.
Collective Response of Human Populations to Large-Scale Emergencies
- BusinessPloS one
- 2011
Real-time changes in communication and mobility patterns in the vicinity of eight emergencies, such as bomb attacks and earthquakes, are identified, comparing these with eight non-emergencies, like concerts and sporting events and finding that communication spikes accompanying emergencies are both spatially and temporally localized.
Data for development reloaded: visual matrix techniques for the exploration and analysis of massive mobile phone data
- Computer Science
- 2015
The final author version and the galley proof are versions of the publication after peer review and the final published version features the final layout of the paper including the volume, issue and page numbers.