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Dataset of Multi-aspect Integrated Migration Indicators

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arxiv 2204.14223 v2 pith:RVVZH4Q4 submitted 2022-04-26 cs.SI physics.soc-ph

Dataset of Multi-aspect Integrated Migration Indicators

D. Goglia (1) , L. Pollacci (1) , A. Sirbu (1) ((1) Computer Science Department , University of Pisa , Pisa , Italy) This is my paper
classification cs.SI physics.soc-ph
keywords migrationdatasetindicatorsdataintegratedmulti-aspectoriginalprocess
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Nowadays, new branches of research are proposing the use of non-traditional data sources for the study of migration trends in order to find an original methodology to answer open questions about the human mobility framework. In this context we presents the Multi-aspect Integrated Migration Indicators (MIMI) dataset, an new dataset of migration drivers, resulting from the process of acquisition, transformation and merge of both official data about international flows and stocks and original indicators not typically used in migration studies, such as online social networks. This work describes the process of gathering, embedding and merging traditional and novel features, resulting in this new multidisciplinary dataset that we believe could significantly contribute to nowcast to forecast both present and future bilateral migration trends.

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