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.

This forward-looking Research Handbook showcases cutting-edge research on the relationship between international migration and digital technology. It sheds new light on the interlinkages between digitalisation and migration patterns and processes globally, capturing the latest research technologies and data sources. Featuring international migration in all facets from the migration of tech sector specialists through to refugee displacement, leading contributors offer strategic insights into the future of migration and mobility.

The book constitutes proceedings of the 12th Industry Symposium held in conjunction with the 18th edition of the International Conference on Distributed Computing and Intelligent Technology (ICDCIT 2022). The focus of the industry symposium is on Mobile Application Development: Practice and Experience. This book focuses on software engineering research and practice supporting any aspects of mobile application development. The book discusses findings in the areas of mobile application analysis, models for generating these applications, testing, debugging & repair, localization & globalization, app review analytics, app store mining, app beyond smartphones and tablets, app deployment, maintenance, and reliability of apps, industrial case studies of automated software engineering for mobile apps, etc. Papers included in the book describe new or improved ways to handle these aspects or address them in a more unified manner, discussing benefits, limitations, and costs of provided solutions. The volume will be useful for master, research students as well as industry professionals.

This open access book explores implications of the digital revolution for migration scholars’ methodological toolkit. New information and communication technologies hold considerable potential to improve the quality of migration research by originating previously non-viable solutions to a myriad of methodological challenges in this field of study. Combining cutting-edge migration scholarship and methodological expertise, the book addresses a range of crucial issues related to both researcher-designed data collections and the secondary use of “big data”, highlighting opportunities as well as challenges and limitations. A valuable source for students and scholars engaged in migration research, the book will also be of keen interest to policymakers.

This book showcases the potential of computational approaches for research questions at the heart of migration and integration research via a set of original, cutting-edge empirical studies by a diverse, international team of authors. Why do people emigrate? Do weather conditions and climate change affect decisions to migrate? How do migration networks evolve on a global scale? Can we predict refugee movements? How do host communities respond to the influx of refugees? Do right-wing populist parties get stronger where lots of refugees are located? Do terror attacks lead to more hostility towards immigrants? What mechanisms explain neighborhood ethnic segregation? The collection of studies in this book harnesses the power of an emerging interdisciplinary research field known as computational social science to shed new light on such classic questions of migration and integration research. The cutting-edge empirical studies use a wide range of computational approaches, from agent-based modeling and network analysis to machine learning, natural language processing, and advanced spatial methods and cover detailed spatial, textual, and network data from both online and offline sources. The book thus demonstrates the potential of computational approaches for migration and integration research, while also discussing the challenges that arise in this emerging field. This book will be an invaluable resource for researchers, students of sociology, ethnic and migration studies, international politics, and computational social science. It was originally published as a special issue of the Journal of Ethnic and Migration Studies.

In this thoroughly revised and updated second edition, William Allen and Carlos Vargas-Silva bring together a diverse range of experts to explore the latest research methods in migration studies, taking stock of major changes that have been salient for migration research—as well as the social sciences more broadly—in the last decade. Spanning a variety of different methodologies, this second edition of the Handbook of Research Methods in Migration provides practical guidance on designing, completing, and communicating migration research, considering diverse audiences including migrants themselves. This title contains one or more Open Access chapters.

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact – identifying a social need, targeting an intervention, measuring impact – and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.