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Behavioral calibration of mobile-phone GPS data for population-representative analyses — arXiv:2609.01042

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.01042
License (as archived): CC0-1.0
Archived: 2026-10-17T06:42:26.981Z
SHA-256 of the archived text: dfa3193da51d6a12a2805b7b0628d64512b9bb5e253e325e4b8f4e3ff04f22a5
Stable URL of this page: https://metraipolis.com/documento/dc_7f421ffc770a

How to cite

Behavioral calibration of mobile-phone GPS data for population-representative analyses — arXiv:2609.01042 — arXiv (en), https://arxiv.org/abs/2609.01042 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_7f421ffc770a (Metraipolis archive dc_7f421ffc770a, sha256 dfa3193da51d6a12a2805b7b0628d64512b9bb5e253e325e4b8f4e3ff04f22a5)

BibTeX

@misc{dc7f421ffc770a,
  title = {Behavioral calibration of mobile-phone GPS data for population-representative analyses — arXiv:2609.01042},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.01042},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_7f421ffc770a; sha256 dfa3193da51d6a12a2805b7b0628d64512b9bb5e253e325e4b8f4e3ff04f22a5},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.01042. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Mobile phone mobility data have transformed the study of human behavior, but demographic and behavioral biases can compromise their representativeness and distort population-level inference. Existing calibration approaches primarily address demographic and geographic representativeness, leaving behavioral discrepancies largely uncorrected. Here we introduce the Behavioral Population (BePop) framework, which jointly calibrates mobility data to representative demographic and behavioral distributions using census data and time-use surveys. BePop embeds mobility sequences into behavioral profiles and estimates person-level weights that align both population composition and daily activity patterns. Across three U.S. metropolitan areas, the framework consistently improves agreement between GPS-derived mobility and representative behavioral distributions, including time allocation, activity transitions, and mobility motifs. Calibration also substantially alters downstream mobility indicators, demonstrating that behavioral biases can propagate into commonly used mobility measures. Our results establish behavioral representativeness as a critical complement to demographic calibration and provide a general framework for population-representative mobility inference.

Tema degli esploratori: governance digitale e beni comuni (retro-catalogo arXiv: annunci del 2026-09-02 in cs.CY).
Categorie arXiv: Physics and Society (physics.soc-ph) ; Computers and Society (cs.CY); Social and Information Networks (cs.SI).
Pagina del lavoro: https://arxiv.org/abs/2609.01042 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T06:36:58.690Z dalla pagina https://arxiv.org/catchup/cs.CY/2026-09-02?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).