*1 Department of Computer Science, University of Pisa, 56127 Pisa, Italy; d.goglia@studenti.unipi.it (D.G.), laura.pollacci@di.unipi.it (L.P.), alina.sirbu@unipi.it (A.S)
MIMI is an integrated dataset of migration drivers, resulting from the process of acquisition, transformation and integration of both official data about bidirectional human mobility (traditional flow and stock data) and multidisciplinary features and original indicators not typically used in migration studies, such as online social networks.
The Python Notebook provided in this repository is useful to read and analyze MIMI dataset.
Dataset: Goglia, D. (2022). Multi-aspect Integrated Migration Indicators (MIMI) dataset (version 2.0.0). Zenodo. https://doi.org/10.5281/zenodo.6493325
Related paper: currently submitted to MDPI Data [status: under revisions]. The link will be available soon.
This work received funding by the European Union – Horizon 2020 Program through the
project “HumMingBird – Enhanced migration measures from a multidimensional perspective”,
Grant Agreement n.870661. and under the scheme “INFRAIA-01-2018-2019 – Integrating Activities
for Advanced Communities”, Grant Agreement n.871042, “SoBigData++: European Integrated
Infrastructure for Social Mining and Big Data Analytics”.
