Seminar series
Date
Tue, 18 Nov 2025
14:00
Location
C4
Speaker
Dongyi Wu and Kristen McCollum
Organisation
Department of Migration Studies, University of Oxford
Dongyi Wu : Homophily and diffusion in migrant–local networks: implications for cross-border investment

Migrant communities shape cross-border investment to their country of origin by reducing

information frictions and attitudes bias. Whether these benefits spill over to locals depends

not only on the size of the diaspora but also on the intensity of interaction between migrants

and locals in the host country. I present a theoretical model with agent-based simulation to

study how homophily between migrants and locals affects information and attitude diffusion

in the host society. I implement varying homophily preferences in a Schelling-style

segregation model and compare two diffusion processes: (i) a simple susceptible–infected

(SI) model for information diffusion; (ii) an adoption-threshold model for attitude diffusion.

For information diffusion, preliminary results indicate that higher homophily slows the

spread and confines diffusion within the migrant group, especially under high segregation. In

the attitude model, adoption varies non-monotonically with homophily. I also provide an

initial analysis of how these patterns interact with different migrant population shares and

seeding rules.

 
Kristen McCollum : The Social Fabric of Mobility: Personal Network Structures in the Democratic Republic of the Congo
The prevailing intuition of the experience of conflict-induced displacement has been one of severance — from home and from its associated relationships. If this is true, it paints a bleak picture of what a displaced person may expect for their future.  Relationships, or social networks, are often cited as being the prime movers for important social and economic outcomes. When displaced people find themselves without their home, job, or basic familiarity with surroundings, this is arguably when the valuable resource of relationships is most needed.  
This paper aims to explore and challenge the current common sense of what the social world of a person displaced by conflict indeed looks like.  The research uses innovative (offline) social network data from eastern DRC, where decades of conflict have resulted in one of the highest internal displacement rates in the world. Using a combination of regression analysis and k-means cluster analysis, I compare the structure of social networks of households across migration status.  The research adds to theory on how social networks relate to critical events.
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