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Exploring the use of mobile phone data for national migration statistics.

ABSTRACT: Statistics on internal migration are important for keeping estimates of subnational population numbers up-to-date as well as urban planning, infrastructure development and impact assessment, among other applications. However, migration flow statistics typically remain constrained by the logistics of infrequent censuses or surveys. The penetration rate of mobile phones is now high across the globe with rapid recent increases in ownership in low-income countries. Analysing the changing spatiotemporal distribution of mobile phone users through anonymized call detail records (CDRs) offers the possibility to measure migration at multiple temporal and spatial scales. Based on a dataset of 72 billion anonymized CDRs in Namibia from October 2010 to April 2014, we explore how internal migration estimates can be derived and modelled from CDRs at subnational and annual scales, and how precision and accuracy of these estimates compare to census-derived migration statistics. We also demonstrate the use of CDRs to assess how migration patterns change over time, with a finer temporal resolution compared to censuses. Moreover, we show how gravity-type spatial interaction models built using CDRs can accurately capture migration flows. Results highlight that estimates of migration flows made using mobile phone data is a promising avenue for complementing more traditional national migration statistics and obtaining more timely and local data.

SUBMITTER: Lai S

PROVIDER: S-EPMC6774788 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Exploring the use of mobile phone data for national migration statistics.

Lai Shengjie S Zu Erbach-Schoenberg Elisabeth E Pezzulo Carla C Ruktanonchai Nick W NW Sorichetta Alessandro A Steele Jessica J Li Tracey T Dooley Claire A CA Tatem Andrew J AJ

Palgrave communications 20190301

Statistics on internal migration are important for keeping estimates of subnational population numbers up-to-date as well as urban planning, infrastructure development and impact assessment, among other applications. However, migration flow statistics typically remain constrained by the logistics of infrequent censuses or surveys. The penetration rate of mobile phones is now high across the globe with rapid recent increases in ownership in low-income countries. Analysing the changing spatiotempo ...[more]

PMID: 31579302

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Project description:Mobile phone use brings convenience to people's social communication and leisurely experience. While excessive mobile phone use also leads to problematic mobile phone use such as mobile phone addiction and nomophobia which has serious harm. For college students who have just entered college, the adaptability to college life and the level of adult attachment might affect mobile phone use. Therefore, it is necessary to study the relationships among mobile phone use, adaptability and adult attachment among college students in China. The data in this article could help researchers explore the mechanism between the mobile phone use, adaptability and adult attachment and had a deeper comprehension to the impact factor of mobile phone use among college students in China. Dataset provided in this article included 673 college students recruited from different grades in Tianjin Normal University. Among the participants, there were 138 males (20.5%) and 535 females. Fifty participants completed their questionnaires as a paper-pencil version in a classroom, there were 389 participants completed paper-pencil version in total and other 284 participants completed online surveys through the Wen Juan Xing App (https://www.wjx.cn). They took Nomophobia Scale for Chinese (NMP-C), Mobile Phone Addiction Tendency Scale (MPATS), Freshmen Adaptation Inventory (FAI) and Chinese of Experiences in Close Relationships Inventory (ECR-C) to measure college students' mobile phone use, adaptability and adult attachment in China, the missing values of these items were imputed by EM method due to the missing values were missing completely at random(MCAR). All the instruments for data collection were in the Chinese version. In addition, a .csv file consists of major variables we used were included as a supplementary material on the Zenodo Repository [1]. We used SPSS to perform descriptive statistical analysis and MPLUS to carry out lasso regression analysis with the collected data. For a discussion of the findings based on the dataset please see the article: The effect of college students' adaptability on nomophobia based on lasso regression [2].

Dataset Information

Exploring the use of mobile phone data for national migration statistics.

Publications

Exploring the use of mobile phone data for national migration statistics.

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