Data Science For Migration And Mobility
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Data Science for Migration and Mobility
Author: Albert Ali Salah
language: en
Publisher: Oxford University Press, USA
Release Date: 2023-02-10
Migration is a complex phenomenon with multi-dimensional factors. With ever-expanding data storage and processing capabilities, new data sources (such as social media, mobile call data records, and satellite imaging) are becoming available to study migration from both qualitative and quantitative perspectives. Data Science for Migration and Mobility addresses the needs of both migration scholars who stand to benefit from the analysis of these new sources but lack the computational tools, as well as data scientists who have practical and theoretical knowledge in dealing with these data sources but have no familiarity with the relevant questions of migration research. It describes the main conceptual frameworks, explains techniques of data collection and processing, provides case studies, discusses the strengths and limitations of each data source, and critically discusses the ethical, legal, and privacy-related issues specific to each data source.
Data Science for Migration and Mobility
Author: Albert Ali Salah
language: en
Publisher: Liverpool University Press
Release Date: 2022-11-10
Data Science for Migration and Mobility provides an interdisciplinary introduction to the usage of new data sources in migration and mobility research, including mobile phone records, social media content, satellite images, event and financial databases.
Guide to Mobile Data Analytics in Refugee Scenarios
After the start of the Syrian Civil War in 2011–12, increasing numbers of civilians sought refuge in neighboring countries. By May 2017, Turkey had received over 3 million refugees — the largest refugee population in the world. Some lived in government-run camps near the Syrian border, but many have moved to cities looking for work and better living conditions. They faced problems of integration, income, welfare, employment, health, education, language, social tension, and discrimination. In order to develop sound policies to solve these interlinked problems, a good understanding of refugee dynamics isnecessary. This book summarizes the most important findings of the Data for Refugees (D4R) Challenge, which was a non-profit project initiated to improve the conditions of the Syrian refugees in Turkey by providing a database for the scientific community to enable research on urgent problems concerning refugees. The database, based on anonymized mobile call detail records (CDRs) of phone calls and SMS messages of one million Turk Telekom customers, indicates the broad activity and mobility patterns of refugees and citizens in Turkey for the year 1 January to 31 December 2017. Over 100 teams from around the globe applied to take part in the challenge, and 61 teams were granted access to the data. This book describes the challenge, and presents selected and revised project reports on the five major themes: unemployment, health, education, social integration, and safety, respectively. These are complemented by additional invited chapters describing related projects from international governmental organizations, technological infrastructure, as well as ethical aspects. The last chapter includes policy recommendations, based on the lessons learned. The book will serve as a guideline for creating innovative data-centered collaborations between industry, academia, government, and non-profit humanitarian agencies to deal with complex problems in refugee scenarios. It illustrates the possibilities of big data analytics in coping with refugee crises and humanitarian responses, by showcasing innovative approaches drawing on multiple data sources, information visualization, pattern analysis, and statistical analysis.It will also provide researchers and students working with mobility data with an excellent coverage across data science, economics, sociology, urban computing, education, migration studies, and more.