IDEAS home Printed from https://ideas.repec.org/p/has/discpr/2116.html
   My bibliography  Save this paper

Inequality is rising where social network segregation interacts with urban topology

Author

Listed:
  • Gergő Tóth

    (Agglomeration and Social Networks Lendület Research Group, Centre for Economic-and Regional Studies, Budapest, Hungaryand Spatial Dynamics Lab, University College Dublin, Dublin, Ireland)

  • Johannes Wachs

    (Institute for Data, Process and Knowledge Management, Vienna University of Economics and Business, Vienna, Austria and Complexity Science Hub Vienna, Vienna, Austria)

  • Riccardo Di Clemente

    (Department of Computer Science, University of Exeter, Exeter, UK and Centre for Advanced Spatial Analysis, University College London, London, UK)

  • Ákos Jakobi

    (Department of Regional Science, Eötvös Loránd University, Budapest, Hungary and Institute of Advanced Studies, Kőszeg, Hungary)

  • Bence Ságvári

    (CSS-Recens, Centre for Social Sciences, Budapest, Hungary and International Business School Budapest, Budapest, Hungary)

  • János Kertész

    (Department of Network and Data Science, Central European University, Budapest, Hungary)

  • Balázs Lengyel

    (Agglomeration and Social Networks Lendület Research Group, Centre for Economic-and Regional Studies, Budapest, Hungary; International Business School Budapest, Budapest, Hungary and NETI Lab, Corvinus Institute for Advanced Studies, Budapest Corvinus University, Budapest, Hungary)

Abstract

Social networks amplify inequalities by fundamental mechanisms of social tie formation such as homophily and triadic closure. These forces sharpen social segregation, which is reflected in fragmented social network structure. Geographical impediments such as distance and physical or administrative boundaries also reinforce social segregation. Yet, less is known about the joint relationships between social network structure, urban geography, and inequality. In this paper we analyze an online social network and find that the fragmentation of social networks is significantly higher in towns in which residential neighborhoods are divided by physical barriers such as rivers and railroads. Towns in which neighborhoods are relatively distant from the center of town and amenities are spatially concentrated are also more socially segregated. Using a two-stage model, we show that these urban geography features have significant relationships with income inequality via social network fragmentation. In other words, the geographic features of a place can compound economic inequalities via social networks.

Suggested Citation

  • Gergő Tóth & Johannes Wachs & Riccardo Di Clemente & Ákos Jakobi & Bence Ságvári & János Kertész & Balázs Lengyel, 2021. "Inequality is rising where social network segregation interacts with urban topology," CERS-IE WORKING PAPERS 2116, Institute of Economics, Centre for Economic and Regional Studies.
  • Handle: RePEc:has:discpr:2116
    as

    Download full text from publisher

    File URL: https://www.mtakti.hu/wp-content/uploads/2021/03/CERSIEWP202116.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kolkowski, Lukas & Cats, Oded & Dixit, Malvika & Verma, Trivik & Jenelius, Erik & Cebecauer, Matej & Rubensson, Isak Jarlebring, 2023. "Measuring activity-based social segregation using public transport smart card data," Journal of Transport Geography, Elsevier, vol. 110(C).
    2. Tanner Regan & Andreas Diemer & Cheng Keat Tang, 2023. "The Role of Social Connections in the Racial Segregation of US Cities," Working Papers 2023-05, The George Washington University, Institute for International Economic Policy.
    3. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    4. Wang, Xi & Pei, Tao & Song, Ci & Chen, Jie & Shu, Hua & Liu, Yaxi & Guo, Sihui & Chen, Xiao, 2023. "How does socioeconomic status influence social relations? A perspective from mobile phone data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    5. Éva Huszti & Fruzsina Albert & Adrienn Csizmady & Ilona Nagy & Beáta Dávid, 2021. "When Spatial Dimension Matters: Comparing Personal Network Characteristics in Different Segregated Areas," Social Inclusion, Cogitatio Press, vol. 9(4), pages 375-387.
    6. Stark, Oded & Bielawski, Jakub & Falniowski, Fryderyk, 2023. "Measuring Income Inequality in Social Networks," IZA Discussion Papers 16666, Institute of Labor Economics (IZA).
    7. Sanghamitra Mukherjee, 2021. "A Framework to Measure Regional Disparities in Battery Electric Vehicle Diffusion in Ireland," Working Papers 202119, School of Economics, University College Dublin.
    8. Tobias Ruttenauer, 2024. "Spatial Data Analysis," Papers 2402.09895, arXiv.org.
    9. Rüttenauer, Tobias, 2023. "Spatial Data Analysis," SocArXiv mq7te, Center for Open Science.

    More about this item

    Keywords

    social networks; income inequality; social segregation; network fragmentation; geographicalcal boundaries; urban topology;
    All these keywords.

    JEL classification:

    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • N34 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: 1913-
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:has:discpr:2116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nora Horvath (email available below). General contact details of provider: https://edirc.repec.org/data/iehashu.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.