research-article

Characterization of internal migrant behavior in the immediate post-migration period using cell phone traces

Authors:

Enrique Frias-Martinez,

Andrés Villarreal,

Vanessa Frias-MartinezAuthors Info & Claims

ICTD '19: Proceedings of the Tenth International Conference on Information and Communication Technologies and Development

Article No.: 4, Pages 1 - 12

https://doi.org/10.1145/3287098.3287119

Published: 04 January 2019 Publication History

Abstract

Internal migrations have been studied using two types of approaches: macro-level and micro-level analyses. Macro-level studies are typically carried out using a combination of various survey and census datasets to model large-scale behaviors, however these models fail to provide more nuanced information about the physical or social status of the migrants. Micro approaches, which successfully use interviews and diaries to provide a window into more individual behaviors, could benefit from methods to identify novel or under-studied behaviors that should be addressed in the migration research agenda. In this paper, we present a framework that uses information extracted from cell phone metadata to reveal internal migration behaviors that could guide or complement the research agenda of micro-level migration researchers working to understand the physical, social and psychological decision processes behind migration experiences. The proposed framework allows to carry out micro-level analyses of internal migration with a focus on immediate post-migration behaviors and the role of pre-migration activities from two perspectives: spatial behaviors and social ties. Ultimately, we expect our analyses to inform migration researchers of pre- and post-migration behaviors that would benefit from further qualitative analysis.

References

[1]

R. Ahas, S. Silm, O. Järv, E. Saluveer, and M. Tiru. 2010. Using mobile positioning data to model locations meaningful to users of mobile phones. Journal of urban technology 17, 1 (2010), 3--27.

[2]

David Akeju. 2013. Africa, internal migration. The Encyclopedia of Human Migration (2013).

[3]

Jeffrey J Axisa, K Bruce Newbold, and Darren M Scott. 2012. Migration, urban growth and commuting distance in Toronto's commuter shed. Area 44, 3 (2012), 344--355.

[4]

Richard D Bedford et al. 2017. New Hebridean Mobility: a study of circular migration. Canberra, ACT: Dept. of Human Geography, Research School of Pacific Studies, The Australian National University.

[5]

Joshua E Blumenstock. 2012. Inferring patterns of internal migration from mobile phone call records: evidence from Rwanda. Information Technology for Development 18, 2 (2012), 107--125.

[6]

A Bonfiglio. 2012. New approaches for researching the determinants of migration processes: ESF strategic workshop on migration research. International Migration Institute, University of Oxford, for European Science Foundation (ESF) (2012).

[7]

George J Borjas, Stephen G Bronars, and Stephen J Trejo. 1992. Self-selection and internal migration in the United States. Journal of urban Economics 32, 2 (1992), 159--185.

[8]

John O Browder, James R Bohland, and Joseph L Scarpaci. 1995. Patterns of development on the metropolitan fringe: Urban fringe expansion in Bangkok, Jakarta, and Santiago. Journal of the American Planning Association 61, 3 (1995), 310--327.

[9]

LA Brown and J Holmes. 1971. Intra-urban migrant lifelines: a spatial view. Demography 8, 1 (1971), 103--122.

[10]

Martin T Cadwallader. 1992. Migration and residential mobility: Macro and micro approaches. Univ of Wisconsin Press.

[11]

Francesco Calabrese, Giusy Di Lorenzo, Liang Liu, and Carlo Ratti. 2011. Estimating Origin-Destination flows using opportunistically collected mobile phone location data from one million users in Boston Metropolitan Area. IEEE Pervasive Computing 10, 4 (2011), 36--44.

Digital Library

[12]

Arul Chib, Holley A Wilkin, and Sri Ranjini Mei Hua. 2013. International migrant workersâĂ&Zacute; use of mobile phones to seek social support in Singapore. Information Technologies & International Development 9, 4 (2013), pp--19.

[13]

Eunjoon Cho, Seth A Myers, and Jure Leskovec. 2011. Friendship and mobility: user movement in location-based social networks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1082--1090.

Digital Library

[14]

Cati Coe. 2011. What is the impact of transnational migration on family life? Women's comparisons of internal and international migration in a small town in Ghana. American Ethnologist 38, 1 (2011), 148--163.

[15]

Jacob Cohen. 1992. A power primer. Psychological bulletin 112, 1 (1992), 155.

[16]

G.F. De Jong and J.T. Fawcett. 1981. Motivations for migration: an assessment and a value-expectancy research model. (1981).

[17]

Yves-Alexandre De Montjoye, César A Hidalgo, Michel Verleysen, and Vincent D Blondel. 2013. Unique in the crowd: The privacy bounds of human mobility. Scientific reports 3 (2013), 1376.

[18]

Bruce Frayne and Wade Pendleton. 2001. Migration in Namibia: Combining macro and micro approaches to research design and analysis. International Migration Review 35, 4 (2001), 1054--1085.

[19]

E. Frias-Martinez and V. Karamcheti. 2002. A customizable behavior model for temporal prediction of web user sequences. In Int. Workshop on Mining Web Data for Discovering Usage Patterns and Profiles. 66--85.

Digital Library

[20]

Vanessa Frias-Martinez, Cristina Soguero-Ruiz, Enrique Frias-Martinez, and Malvina Josephidou. 2013. Forecasting socioeconomic trends with cell phone records. In Proc. 3rd ACM Symp. Computing for Development. ACM, 15.

Digital Library

[21]

Vanessa Frias-Martinez and Jesus Virseda. 2013. Cell phone analytics: Scaling human behavior studies into the millions. Information Technologies & International Development 9, 2 (2013), pp--35.

[22]

V. Frias-Martinez, J. Virseda, A. Rubio, and E. Frias-Martinez. 2010. Towards large scale technology impact analyses: Automatic residential localization from mobile phone-call data. In 4th ACM/IEEE Intl. Conf. Inf. and Communication technologies and development. ACM, 11.

Digital Library

[23]

M. Gonzalez, C. Hidalgo, and A.-L. Barabasi. 2008. Understanding individual human mobility patterns. nature 453, 7196 (2008), 779.

[24]

Nicola Green. 2002. On the move: Technology, mobility, and the mediation of social time and space. The information society 18, 4 (2002), 281--292.

[25]

Michael J Greenwood. 1975. Research on internal migration in the United States: a survey. Journal of Economic Literature (1975), 397--433.

[26]

GSMA. {n. d.}. GSMA Country Overview: Mexico, Mobile Driving Growth, Innovation and Opportunity. https://www.gsma.com/latinamerica/wp-content/uploads/2016/06/report-mexico2016-EN.pdf. Accessed: 04-10-2018.

[27]

Douglas T Gurak and Fee Caces. 1992. Migration networks and the shaping of migration systems. International migration systems: A global approach (1992), 150--176.

[28]

Joseph F Hair, William C Black, Barry J Babin, Rolph E Anderson, Ronald L Tatham, et al. 2006. Multivariate data analysis (Vol. 6). Upper Saddle River, NJ: Pearson Prentice Hall.

Digital Library

[29]

Martijn Hendriks, Kai Ludwigs, and Ruut Veenhoven. 2016. Why are locals happier than internal migrants? The role of daily life. Social Indicators Research 125, 2 (2016), 481--508.

[30]

Prue Holmes and Annick Janson. 2008. Migrants' communication practices with ICTs: tools for facilitating migration and adaptation? International journal of technology, knowledge & society. 4, 6 (2008), 51--62.

[31]

Emma Hopkins, Francesca Bastagli, and Jessica Hagen-Zanker. 2016. Internal migrants and social protection: a review of eligibility and take-up. Technical Report. ODI Working Paper.

[32]

G. Hugo. 2013. What we know about circular migration and enhanced mobility. Migration Policy Institute 7 (2013).

[33]

Mexican Statistical Institute INEGI. 2013. 2010 Census of Population and Housing Units. http://en.www.inegi.org.mx/proyectos/ccpv/2010/. Accessed: 2017-09-12.

[34]

Mexican Statistical Institute INEGI. 2015. National Survey of Demographic Dynamics 2014. http://www.beta.inegi.org.mx/proyectos/enchogares/especiales/enadid/2014/default.html. Accessed: 2017-06-15.

[35]

S. Isaacman, R. Becker, R. Caceres, S. Kobourov, J. Martonosi, M.and Rowland, and A. Varshavsky. 2011. Identifying important places in peoples lives from cellular network data. In Int. Conf. on Pervasive Computing. 133--151.

Digital Library

[36]

Ben CH Kuo. 2014. Coping, acculturation, and psychological adaptation among migrants: a theoretical and empirical review and synthesis of the literature. Health Psychology and Behavioral Medicine 2, 1 (2014), 16--33.

[37]

Wen H Kuo and Yung-Mei Tsai. 1986. Social networking, hardiness and immigrant's mental health. Journal of health and social behavior (1986), 133--149.

[38]

M. Lenormand, A. Bassolas, and J.J. Ramasco. 2016. Systematic comparison of trip distribution laws and models. J. Transport Geography 51 (2016), 158--169.

[39]

M. Lenormand, S. Huet, F. Gargiulo, and G. Deffuant. 2012. A universal model of commuting networks. PloS one 7, 10 (2012), e45985.

[40]

Maxime Lenormand, Miguel Picornell, Oliva G Cantú-Ros, Thomas Louail, Ricardo Herranz, Marc Barthelemy, Enrique Frías-Martínez, Maxi San Miguel, and José J Ramasco. 2015. Comparing and modelling land use organization in cities. Royal Society open science 2, 12 (2015), 150449.

[41]

Shengxiao Li and Pengjun Zhao. 2018. Restrained mobility in a high-accessible and migrant-rich area in downtown Beijing. European transport research review 10, 1 (2018), 4.

[42]

Yanwei Lin, Qi Zhang, Wen Chen, Jingrong Shi, Siqi Han, Xiaolei Song, Yong Xu, and Li Ling. 2016. Association between social integration and health among internal migrants in ZhongShan, China. PloS one 11, 2 (2016), e0148397.

[43]

Jennifer Mason. 2004. Managing kinship over long distances: the significance of âĂ&Yuml;the visitâĂ&Zacute;. Social Policy and Society 3, 4 (2004), 421--429.

[44]

Dipak Mazumdar. 1976. The urban informal sector. World development 4, 8 (1976), 655--679.

[45]

Raven Molloy, Christopher L Smith, and Abigail Wozniak. 2011. Internal migration in the United States. Journal of Economic perspectives 25, 3 (2011), 173--96.

[46]

Raul Montoliu and Daniel Gatica-Perez. 2010. Discovering human places of interest from multimodal mobile phone data. In Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia. ACM, 12.

Digital Library

[47]

J.M. Nogle. 1994. Internal migration for recent immigrants to Canada. International Migration Review (1994), 31--48.

[48]

J-P Onnela, Jari Saramäki, Jorkki Hyvönen, György Szabó, David Lazer, Kimmo Kaski, János Kertész, and A-L Barabási. 2007. Structure and tie strengths in mobile communication networks. Proc. Nat. Academy of Sciences 104, 18 (2007), 7332--7336.

[49]

David A Plane. 1984. Migration space: Doubly constrained gravity model mapping of relative interstate separation. Annals of the Association of American Geographers 74, 2 (1984), 244--256.

[50]

A. Rubio, V. Frias-Martinez, E. Frias-Martinez, and N. Oliver. 2010. Human Mobility in Advanced and Developing Economies: A Comparative Analysis. In AAAI Spring Symposium: Artificial Intelligence for Development.

[51]

RM Sakia. 1992. The Box-Cox transformation technique: a review. The statistician (1992), 169--178.

[52]

George AF Seber and Alan J Lee. 2012. Linear regression analysis. Vol. 329. John Wiley & Sons.

[53]

F. Simini, M.C. González, A. Maritan, and A.lbert-László Barabási. 2012. A universal model for mobility and migration patterns. Nature 484, 7392 (2012), 96.

[54]

Ronald Skeldon. 2014. Migration and development: A global perspective. Routledge.

[55]

Ronald Skeldon. 2017. International Migration, internal migration, mobility and urbanization:towards more integrated approaches. Population Division, Department of Economic and Social Affairs, United Nations (2017).

[56]

S.A. Stouffer. 1940. Intervening opportunities: a theory relating mobility and distance. American sociological review 5, 6 (1940), 845--867.

[57]

Waldo Tobler. 1995. Migration: Ravenstein, thornthwaite, and beyond. Urban Geography 16, 4 (1995), 327--343.

[58]

Michael Todaro. 1980. Internal migration in developing countries: a survey. In Population and economic change in developing countries. University of Chicago Press, 361--402.

[59]

Zeynep Tufekci. 2014. Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls. ICWSM 14 (2014), 505--514.

[60]

Steven Vertovec. 2004. Cheap calls: the social glue of migrant transnationalism. Global networks 4, 2 (2004), 219--224.

[61]

Ingmar Weber, Emilio Zagheni, et al. 2013. Studying inter-national mobility through IP geolocation. In Proceedings of the sixth ACM international conference on Web search and data mining. ACM, 265--274.

Digital Library

[62]

Yingxiang Yang, Carlos Herrera, Nathan Eagle, and Marta C González. 2014. Limits of predictability in commuting flows in the absence of data for calibration. Scientific reports 4 (2014), 5662.

[63]

Emilio Zagheni, Venkata Rama Kiran Garimella, Ingmar Weber, et al. 2014. Inferring international and internal migration patterns from twitter data. In Proceedings of the 23rd International Conference on World Wide Web. ACM, 439--444.

Digital Library

[64]

Emilio Zagheni and Ingmar Weber. 2012. You are where you e-mail: using e-mail data to estimate international migration rates. In Proceedings of the 4th Annual ACM Web Science Conference. ACM, 348--351.

Digital Library

[65]

Cathy Zimmerman, Ligia Kiss, and Mazeda Hossain. 2011. Migration and health: a framework for 21st century policy-making. PLOS medicine 8, 5 (2011), e1001034.

[66]

Donald W Zimmerman and Bruno D Zumbo. 1993. Rank transformations and the power of the Student t test and Welch t'test for non-normal populations with unequal variances. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale 47, 3 (1993), 523.

[67]

G.K. Zipf. 1946. On the intercity movement of persons. American sociological review 11, 6 (1946), 677--686.

Cited By

Arcila-Calderón CAydoğdu BBircan TGündüz BÖnes OSalah ASîrbu A(2025)Combining Twitter and mobile phone data to observe border-rush: the Turkish-European border openingJournal of Computational Social Science10.1007/s42001-024-00354-88:1Online publication date: 30-Jan-2025
https://doi.org/10.1007/s42001-024-00354-8
Dias VFernando LLin YFrias-Martinez VRaschid L(2023)Framework to Study Migration Decisions Using Call Detail Record (CDR) DataIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.317772710:5(2725-2738)Online publication date: Oct-2023
https://doi.org/10.1109/TCSS.2022.3177727
Reymondin LVantalon TPham HLe HHuynh THernandez REven BNguyen TPhan TNguyen KBéné C(2023)Using free Wi-Fi to assess impact of COVID-19 pandemic on traditional wet markets in HanoiFood Security10.1007/s12571-023-01417-w16:1(223-241)Online publication date: 28-Dec-2023
https://doi.org/10.1007/s12571-023-01417-w
Show More Cited By

Index Terms

Characterization of internal migrant behavior in the immediate post-migration period using cell phone traces
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Empirical studies in ubiquitous and mobile computing

Recommendations

Post-copy live migration of virtual machines

We present the design, implementation, and evaluation of post-copy based live migration for virtual machines (VMs) across a Gigabit LAN. Post-copy migration defers the transfer of a VM's memory contents until after its processor state has been sent to ...
Post-copy based live virtual machine migration using adaptive pre-paging and dynamic self-ballooning
VEE '09: Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments

We present the design, implementation, and evaluation of post-copy based live migration for virtual machines (VMs) across a Gigabit LAN. Live migration is an indispensable feature in today's virtualization technologies. Post-copy migration defers the ...
Pre-Copy and post-copy VM live migration for memory intensive applications
Euro-Par'12: Proceedings of the 18th international conference on Parallel processing workshops

Virtualization technology provides a means for server consolidation, reducing the number of physical servers required for running a given workload. Virtual Machine (VM) live migration facilitates the transfer of a running (VM) between physical hosts ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

ICTD '19: Proceedings of the Tenth International Conference on Information and Communication Technologies and Development

January 2019

422 pages

ISBN:9781450361224

DOI:10.1145/3287098

Conference Chairs:
Rajesh Chandwani
IIM Ahmedabad, India
,
Pushpendra Singh
IIIT Delhi, India
,
Program Chairs:
Neha Kumar
Georgia Institute of Technology, USA
,
Rajesh Veeraraghavan
Georgetown University, USA

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 January 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICTD '19

ICTD '19: Tenth International Conference on Information and Communication Technologies and Development

January 4 - 7, 2019

Ahmedabad, India

Acceptance Rates

Overall Acceptance Rate 22 of 116 submissions, 19%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
150
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Arcila-Calderón CAydoğdu BBircan TGündüz BÖnes OSalah ASîrbu A(2025)Combining Twitter and mobile phone data to observe border-rush: the Turkish-European border openingJournal of Computational Social Science10.1007/s42001-024-00354-88:1Online publication date: 30-Jan-2025
https://doi.org/10.1007/s42001-024-00354-8
Dias VFernando LLin YFrias-Martinez VRaschid L(2023)Framework to Study Migration Decisions Using Call Detail Record (CDR) DataIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.317772710:5(2725-2738)Online publication date: Oct-2023
https://doi.org/10.1109/TCSS.2022.3177727
Reymondin LVantalon TPham HLe HHuynh THernandez REven BNguyen TPhan TNguyen KBéné C(2023)Using free Wi-Fi to assess impact of COVID-19 pandemic on traditional wet markets in HanoiFood Security10.1007/s12571-023-01417-w16:1(223-241)Online publication date: 28-Dec-2023
https://doi.org/10.1007/s12571-023-01417-w
Tai XMehra SBlumenstock J(2022)Mobile phone data reveal the effects of violence on internal displacement in AfghanistanNature Human Behaviour10.1038/s41562-022-01336-46:5(624-634)Online publication date: 12-May-2022
https://doi.org/10.1038/s41562-022-01336-4
Fudolig MMonsivais DBhattacharya KJo HKaski K(2021)Internal migration and mobile communication patterns among pairs with strong tiesEPJ Data Science10.1140/epjds/s13688-021-00272-z10:1Online publication date: 1-Apr-2021
https://doi.org/10.1140/epjds/s13688-021-00272-z
Chi GLin FChi GBlumenstock J(2020)A general approach to detecting migration events in digital trace dataPLOS ONE10.1371/journal.pone.023940815:10(e0239408)Online publication date: 2-Oct-2020
https://doi.org/10.1371/journal.pone.0239408
Igartua MMendoza FRedondo RVicente MForne JCampo CFernandez-Vilas ADe La Cruz Llopis LGarcia-Rubio CLopez AMezher ADiaz-Sanchez DCerezo-Costas HRebollo-Monedero DArias-Cabarcos PRico-Novella F(2020)INRISCO: INcident monitoRing in Smart COmmunitiesIEEE Access10.1109/ACCESS.2020.29874838(72435-72460)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2987483

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten