Literature DB >> 32203523

Migrant mobility flows characterized with digital data.

Mattia Mazzoli1, Boris Diechtiareff2, Antònia Tugores1, Willian Wives2, Natalia Adler3, Pere Colet1, José J Ramasco1.   

Abstract

Monitoring migration flows is crucial to respond to humanitarian crisis and to design efficient policies. This information usually comes from surveys and border controls, but timely accessibility and methodological concerns reduce its usefulness. Here, we propose a method to detect migration flows worldwide using geolocated Twitter data. We focus on the migration crisis in Venezuela and show that the calculated flows are consistent with official statistics at country level. Our method is versatile and far-reaching, as it can be used to study different features of migration as preferred routes, settlement areas, mobility through several countries, spatial integration in cities, etc. It provides finer geographical and temporal resolutions, allowing the exploration of issues not contemplated in official records. It is our hope that these new sources of information can complement official ones, helping authorities and humanitarian organizations to better assess when and where to intervene on the ground.

Entities:  

Year:  2020        PMID: 32203523      PMCID: PMC7089540          DOI: 10.1371/journal.pone.0230264

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  23 in total

1.  Human diffusion and city influence.

Authors:  Maxime Lenormand; Bruno Gonçalves; Antònia Tugores; José J Ramasco
Journal:  J R Soc Interface       Date:  2015-08-06       Impact factor: 4.118

2.  Promises and Pitfalls of Using Digital Traces for Demographic Research.

Authors:  Nina Cesare; Hedwig Lee; Tyler McCormick; Emma Spiro; Emilio Zagheni
Journal:  Demography       Date:  2018-10

3.  INTERNATIONAL MIGRATION. International migration under the microscope.

Authors:  Frans Willekens; Douglas Massey; James Raymer; Cris Beauchemin
Journal:  Science       Date:  2016-05-20       Impact factor: 47.728

4.  Influence of sociodemographic characteristics on human mobility [corrected].

Authors:  Maxime Lenormand; Thomas Louail; Oliva G Cantú-Ros; Miguel Picornell; Ricardo Herranz; Juan Murillo Arias; Marc Barthelemy; Maxi San Miguel; José J Ramasco
Journal:  Sci Rep       Date:  2015-05-20       Impact factor: 4.379

5.  From mobile phone data to the spatial structure of cities.

Authors:  Thomas Louail; Maxime Lenormand; Oliva G Cantu Ros; Miguel Picornell; Ricardo Herranz; Enrique Frias-Martinez; José J Ramasco; Marc Barthelemy
Journal:  Sci Rep       Date:  2014-06-13       Impact factor: 4.379

6.  Tweets on the road.

Authors:  Maxime Lenormand; Antònia Tugores; Pere Colet; José J Ramasco
Journal:  PLoS One       Date:  2014-08-20       Impact factor: 3.240

7.  Geo-located Twitter as proxy for global mobility patterns.

Authors:  Bartosz Hawelka; Izabela Sitko; Euro Beinat; Stanislav Sobolevsky; Pavlos Kazakopoulos; Carlo Ratti
Journal:  Cartogr Geogr Inf Sci       Date:  2014-02-26

8.  Who Tweets with Their Location? Understanding the Relationship between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter.

Authors:  Luke Sloan; Jeffrey Morgan
Journal:  PLoS One       Date:  2015-11-06       Impact factor: 3.240

9.  Exploring universal patterns in human home-work commuting from mobile phone data.

Authors:  Kevin S Kung; Kael Greco; Stanislav Sobolevsky; Carlo Ratti
Journal:  PLoS One       Date:  2014-06-16       Impact factor: 3.240

10.  A stochastic model of randomly accelerated walkers for human mobility.

Authors:  Riccardo Gallotti; Armando Bazzani; Sandro Rambaldi; Marc Barthelemy
Journal:  Nat Commun       Date:  2016-08-30       Impact factor: 14.919

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  3 in total

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Authors:  Xiao Hui Tai; Shikhar Mehra; Joshua E Blumenstock
Journal:  Nat Hum Behav       Date:  2022-05-12

2.  How do city-specific factors affect migrant integration in China? A study based on a hierarchical linear model of migrants and cities.

Authors:  Rumin Zheng; Lin Mei; Yanhua Guo; Shuo Zhen; Zhanhui Fu
Journal:  PLoS One       Date:  2021-01-12       Impact factor: 3.240

3.  A data fusion approach to the estimation of temporary populations: An application to Australia.

Authors:  Elin Charles-Edwards; Jonathan Corcoran; Julia Loginova; Radoslaw Panczak; Gentry White; Alexander Whitehead
Journal:  PLoS One       Date:  2021-11-11       Impact factor: 3.240

  3 in total

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