Temporal and spatial analysis of indicators on segregation of Syrian refugees in Turkey with mobile phone data

被引：1

作者：

Aydogdu, Bilgecag ^{[1
]}

Ahat, Betul ^{[2
]}

Salah, Albert Ali ^{[1
,3
]}

Bircan, Tuba ^{[4
]}

机构：

[1] Univ Utrecht, Utrecht, Netherlands

[2] Turkcell, Istanbul, Turkey

[3] Bogazici Univ, Istanbul, Turkey

[4] Vrije Univ Brussel, Brussels, Belgium

来源：

2022 30TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU | 2022年

关键词：

Mobile data; Indicators; Migration; Segregation; Computational Social Science; ETHNIC SEGREGATION; DIMENSIONS;

D O I：

10.1109/SIU55565.2022.9864756

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Measuring and monitoring immigrant integration is important for evidence based policy making. Mobile data proposes a valuable opportunity for developing fine grained indicators of segregation and integration of sub-populations. Due to privacy and ethical reasons, mobile phone data is rarely shared with researchers. In this study, we use anonymous and aggregated data sets prepared using mobile positioning data (XDR) collected by Turkcell throughout 2020 with the purpose of calculating different indicators of segregation for refugees in order to understand the temporal and spatial variation of these indicators. In this study, isolation index and dissimilarity index were calculated and compared in terms of their measure of migrant segregation.

引用

页数：4

共 50 条

[31] Ambient Population and Larceny-Theft: A Spatial Analysis Using Mobile Phone Data
He, Li
Paez, Antonio
Jiao, Jianmin
An, Ping
Lu, Chuntian
Mao, Wen
Long, Dongping
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2020, 9 (06)
[32] Analysis of the Spatial Heterogeneity of Commuting Flows in Beijing: Perspectives from Mobile Phone Data
Guo, Sihui
Huang, Qiang
Wen, Congcong
SENSORS AND MATERIALS, 2024, 36 (10) : 4455 - 4471
[33] The temporal variation of ethnic segregation in a city: Evidence from a mobile phone use dataset
Silm, Siiri
Ahas, Rein
SOCIAL SCIENCE RESEARCH, 2014, 47 : 30 - 43
[34] TRAcME: Temporal Activity Recognition using Mobile Phone Data
Choujaa, Driss
Dulay, Naranker
EUC 2008: PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING, VOL 1, MAIN CONFERENCE, 2008, : 119 - 126
[35] A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data
Li, Weifeng
Cheng, Xiaoyun
Duan, Zhengyu
Yang, Dongyuan
Guo, Gaohua
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2014, 2014
[36] Temporal Intersections of Mobility and Informality: Simsars as (Im)moral Agents in the Trajectories of Syrian Refugees in Turkey and Germany
Alkan, Hilal
MIGRATION LETTERS, 2021, 18 (02) : 201 - 213
[37] Working and residential segregation of migrants in Longgang City, China: A mobile phone data-based analysis
Zhang, Yongping
Song, Yang
Zhang, Weiwen
Wang, Xiaoliang
CITIES, 2024, 144
[38] Spatial and Temporal Exploratory Factor Analysis of Urban Mobile Data Traffic
Angelo Furno
André Felipe Zanella
Razvan Stanica
Marco Fiore
Data Science for Transportation, 2024, 6 (1):
[39] Measuring Spatial Subdivisions in Urban Mobility with Mobile Phone Data
Graells-Garrido, Eduardo
Meta, Irene
Serra-Buriel, Feliu
Reyes, Patricio
Cucchietti, Fernando M.
WWW'20: COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2020, 2020, : 485 - 494
[40] Using Mobile Phone Data to Predict the Spatial Spread of Cholera
Linus Bengtsson
Jean Gaudart
Xin Lu
Sandra Moore
Erik Wetter
Kankoe Sallah
Stanislas Rebaudet
Renaud Piarroux
Scientific Reports, 5

← 1 2 3 4 5 →