Abstract
We explore various means of quantifying integration using two of the D4R Challenge datasets. We propose various integration indices and discuss their output. We combine the data from the D4R Challenge with data from the GDELT Project and with data on transactions on the housing market in Turkey. We also describe research directions to be undertaken in the future using the D4R data.
The findings in this paper do not necessarily represent the views of the World Bank’s Board of Executive Directors or the governments they represent. Any errors or omissions are the authors’ responsibility.
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Notes
- 1.
At times, we refer to this group also as natives.
- 2.
The propensity is defined as the average number of calls a type of user performs toward another type of user.
- 3.
Data are mostly missing for “month” 2 and 3 so they are dropped.
- 4.
This happens even if we allow the number of within-group calls for R users, i.e., \(m_{it}(R,R)\), to be a quadratic function of the number of R users in the sample.
- 5.
We have computed an Herfindahl-Hirschmann Index of the concentration across Turkish provinces of R users in the sample for each 2-week sample in Dataset 2; higher (lower) number of R users in the sample is associated with a lower (higher) value of the Herfindahl-Hirschmann Index, revealing a weaker (stronger) concentration.
- 6.
Equation (10.2) that omits the time subscript, but the index \(D_i\) is actually time-varying.
- 7.
Working hours are defined as 8 am–5 pm, all other hours are assigned as non-working.
- 8.
The data come from REIDIN Data and Analytics, a leading provider of real-estate data and information for emerging markets, under a confidentiality agreement.
References
Bell W (1954) A probability model for the measurement of ecological segregation. Soc Forces 32(4):357–364
Chiswick BR (1978) The effect of Americanization on the earnings of foreign-born men. J Polit Econ 86(5):897–921
Duncan OD, Duncan B (1955a) A methodological analysis of segregation indexes. Am Soc Rev 20(2):210–217
Duncan OD, Duncan B (1955b) Residential distribution and occupational stratification. Am J Soc 60(5):493–503
Krackhardt D, Stern RN (1988) Informal networks and organizational crises: an experimental simulation. Soc Psychol Quart 51(2):123–140
Massey DS, Denton NA (1988) The dimensions of residential segregation. Soc Forces 67(2):281–315
Salah A, Pentland A, Lepri B, Letouzé E, Vinck P, de Montjoye Y, Dong X, Da delen O (2018) Data for refugees: the D4R challenge on mobility of Syrian refugees in Turkey. Arxiv preprint arXiv:1807.00523
World Bank (2018) Moving for prosperity: global migration and labor markets (Policy Research Reports). World Bank Publications, http://www.worldbank.org/en/research/publication/moving-for-prosperity
Acknowledgements
This work was supported by the European Commission through the Horizon2020 European project “SoBigData Research Infrastructure—Big Data and Social Mining Ecosystem” (grant agreement 654024).
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Bertoli, S. et al. (2019). Integration of Syrian Refugees: Insights from D4R, Media Events and Housing Market Data. In: Salah, A., Pentland, A., Lepri, B., Letouzé, E. (eds) Guide to Mobile Data Analytics in Refugee Scenarios. Springer, Cham. https://doi.org/10.1007/978-3-030-12554-7_10
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DOI: https://doi.org/10.1007/978-3-030-12554-7_10
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