Living on the other side of the tracks – Study shows how urban topology influences the formation of social networks and inequality
Vienna, February 19, 2020 – A new study shows how the structural factor of urban topology plays a role in facilitating fragmentation and inequality. While it has already been proven that social networks amplify inequalities due to fundamental mechanisms of social tie formation such as homophily (befriending similar people) and triadic closure (befriending friends of friends), a paper published by Nature Communications on February 18 by an international group of scientists demonstrates by using big data from a widely-used online social network, that a significant relationship exists between social network fragmentation and income inequality in cities and towns. Moreover, the researchers have found that the organization of the physical urban space has a stronger relationship with fragmentation than unequal access to education, political segregation, or the presence of ethnic and religious minorities.
“Social scientists are trying to understand the reason behind the persistence and growth of inequalities, and whether it is possible to create policies that could act against them. We know from earlier studies that social networks, as they emerge, not only reflect these inequalities but contribute to their robustness and persistence. Our aim with the research was to investigate if there are other components on the top of social networks that act towards stabilizing these social networks which create the robustness of inequalities,” explains Professor Janos Kertesz from the CEU Department of Network and data Science, one of the authors of the paper.
In the study entitled “Inequality is rising where social network segregation interacts with urban topology” the researchers argue that fragmentation of social networks is significantly higher in towns in which residential neighborhoods are divided by physical barriers such as rivers and/or railroads, and are relatively distant from the center of town. Also, towns in which amenities are spatially concentrated are typically more socially segregated.
“According to urban sociology research, people cannot easily build social ties when they are separated by large physical obstacles such as rivers, railways, highways or walls,” says CEU alumnus Johannes Wachs currently at the Institute for Data, Process and Knowledge Management of Vienna University of Economics and Business and another author of the paper. “This was confirmed in our research: we could see evidence of strong physical boundaries in a city just by looking at its social network. We hypothesized - and confirm it with our findings - that if valuable ideas and information cannot float freely through a city because that city is physically fragmented, it in turn causes social fragmentation, which we will see in inequality. We clearly see how strongly geography and income inequality are related.”
The findings of the paper suggest how urban planning could be a useful point of intervention to mitigate inequalities in the long run, and how “smart city projects” that build massively on the collection and evaluation of large amounts of data should also build on social network data so that urban planning can make cities better functioning and places of better life quality.
Affiliation of the researchers:
Gergo Toth, Agglomeration and Social Networks Lendulet Research Group, Center for Economic and Regional Studies, Budapest, Hungary / Spatial Dynamics Lab, University College, Dublin, Ireland
Johannes Wachs, Institute for Data, Process and Knowledge Management, Vienna University of Economics and Business, Austria / Complexity Science Hub (CSH) Vienna, Austria
Riccardo Di Clemente, Department of Computer Science, University of Exeter, UK / Center for Advanced Spatial Analysis, University College London, UK
Akos Jakobi, Department of Regional Science, Eotvos Lorand University (ELTE), Hungary / Institute of Advanced Studies, Koszeg, Hungary
Bence Sagvari, Agglomeration and Social Networks Lendulet Research Group, Center for Economic and Regional Studies, Budapest, Hungary / CSS-Recens, Center for Social Sciencws, Budapest, Hungary / International Business School, Budapest, Hungary
Janos Kertesz, Department of Network and data Science, Central European University (CEU), Vienna, Austria
Balazs Lengyel, Agglomeration and Social Networks Lendulet Research Group, Center for Economic and Regional Studies, Budapest, Hungary / International Business School, Budapest, Hungary / Neti Lab, Corvinus Institute for Advanced Studies, Corvinus University, Budapest, Hungary