A survey of results on mobile phone datasets analysis
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Abstract (arXiv)
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 of large-scale anonymized datasets, and has grown into a stand-alone topic. We will survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Feb 2015.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 2.
6 papers.
- 2022Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?cited by 2
- 2021Understanding peacefulness through the world newscited by 0
- 2023Predicting Socio-Economic Well-being Using Mobile Apps Data: A Case Study of Francecited by 0
- 2025Temporal social network modeling of mobile connectivity data with graph neural networkscited by 0
- 2026Cellular Predictions on the Move: What about Data?cited by 0
- 2026ABC: Numerical Data Collection under Local Differential Privacy without Prior Knowledgecited by 0
- 2026ABC: Numerical Data Collection under Local Differential Privacy without Prior Knowledge6 Aug 2026
- 2026Cellular Predictions on the Move: What about Data?24 Jun 2026
- 2025Temporal social network modeling of mobile connectivity data with graph neural networks3 Sep 2025
- 2023Predicting Socio-Economic Well-being Using Mobile Apps Data: A Case Study of France15 Jan 2023
- 2022Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?1 May 2022
- 2021Understanding peacefulness through the world news1 Jun 2021