Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

Corentin Cot, Giacomo Cacciapaglia, Francesco Sannino

Open source

DOI: 10.1038/s41598-021-83441-4
Published: 2021-02-18
Container: Scientific Reports
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-021-83441-4,
  title = {Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing},
  author = {Corentin Cot and Giacomo Cacciapaglia and Francesco Sannino},
  year = {2021},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-021-83441-4},
  url = {https://doi.org/10.1038/s41598-021-83441-4}
}

RIS

TY  - JOUR
TI  - Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
AU  - Corentin Cot
AU  - Giacomo Cacciapaglia
AU  - Francesco Sannino
PY  - 2021
JO  - Scientific Reports
DO  - 10.1038/s41598-021-83441-4
UR  - https://doi.org/10.1038/s41598-021-83441-4
ER  -

APA

Cot, C., Cacciapaglia, G., & Sannino, F. (2021). Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing. Scientific Reports. https://doi.org/10.1038/s41598-021-83441-4

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crossref · retrieved 2026-11-10T11:15:43.616Z