Assessing Refugees’ Integration via Spatio-Temporal Similarities of Mobility and Calling Behaviors
Name
1907.06929.pdf
Description
Accepted version
Size
1.05 MB
Format
Adobe PDF
Checksum (MD5)
40b03994397e4f3c7f9e0409c56a9907
Author(s)
Alfeo, Antonio Luca
Cimino, Mario GCA
Lepri, Bruno
Pentland, Alexander Sandy
Vaglini, Gigliola
Date Issued
2019
Journal
IEEE Transactions on Computational Social Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Author's final manuscript
Abstract
© 2019 IEEE. In Turkey, the increasing tension, due to the presence of 3.4 million Syrian refugees, demands the formulation of effective integration policies. Moreover, their design requires tools aimed at understanding the integration of refugees despite the complexity of this phenomenon. In this work, we propose a set of metrics aimed at providing insights and assessing the integration of Syrian refugees, by analyzing a real-world call detail record (CDR) dataset including calls from refugees and locals in Turkey throughout 2017. Specifically, we exploit the similarity between refugees' and locals' spatial and temporal behaviors, in terms of communication and mobility in order to assess integration dynamics. Together with the already known methods for data analysis, we use a novel computational approach to analyze spatio-temporal patterns: Computational stigmergy, a bio-inspired scalar and temporal aggregation of samples. Computational stigmergy associates each sample with a virtual pheromone deposit (mark). Marks in spatiotemporal proximity are aggregated into functional structures called trails, which summarize the spatiotemporal patterns in data and allow computing the similarity between different patterns. According to our results, collective mobility and behavioral similarity with locals have great potential as measures of integration, since they are: 1) correlated with the amount of interaction with locals; 2) an effective proxy for refugee's economic capacity, and thus refugee's potential employment; and 3) able to capture events that may disrupt the integration phenomena, such as social tension.
MIT Department
MIT Connection Science (Research institute)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TCSS.2019.2923216
