期刊
EPJ DATA SCIENCE
卷 3, 期 1, 页码 -出版社
SPRINGEROPEN
DOI: 10.1140/epjds31
关键词
predictive human mobility; social networks; cultural diversity
资金
- Ericsson
- MIT SMART Program
- Center for Complex Engineering Systems (CCES) at KACST
- Center for Complex Engineering Systems (CCES) at MIT CCES program
- National Science Foundation
- MIT Portugal Program
- ATT Foundation
- Audi Volkswagen
- BBVA
- Coca Cola Company
- Expo
- Ferrovial
- Regional Municipality of Wood Buffalo
This study leverages mobile phone data to analyze human mobility patterns in a developing nation, especially in comparison to those of a more industrialized nation. Developing regions, such as the Ivory Coast, are marked by a number of factors that may influence mobility, such as less infrastructural coverage and maturity, less economic resources and stability, and in some cases, more cultural and language-based diversity. By comparing mobile phone data collected from the Ivory Coast to similar data collected in Portugal, we are able to highlight both qualitative and quantitative differences in mobility patterns - such as differences in likelihood to travel, as well as in the time required to travel - that are relevant to consideration on policy, infrastructure, and economic development. Our study illustrates how cultural and linguistic diversity in developing regions (such as Ivory Coast) can present challenges to mobility models that perform well and were conceptualized in less culturally diverse regions. Finally, we address these challenges by proposing novel techniques to assess the strength of borders in a regional partitioning scheme and to quantify the impact of border strength on mobility model accuracy.
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