A large literature uses exogenous variation to estimate how assignment to classrooms or other groups shapes social networks. Yet most of these analyses remain dyadic, treating each link in isolation, even though ties often form through triadic closure, as a friend of a friend also becomes a friend. Using fine-grained data on phone calls, text messages, physical co-location, and social-media ties, we estimate the network formation effects of randomly assigning first-year university students to classrooms and to smaller social groups. To analyze explicitly whether group assignment interact with triadic closure, we use our random assignment to estimate a subgraph generated model of network formation. Accounting for triadic closure turns out to be crucial. For social groups in particular, group assignment affects network formation almost entirely by inducing additional triadic closure. Estimates ignoring triadic closure can thus yield misleading predictions about the network effects and benefits of group assignment policies.
Theoretical and computational models predict that social-network topology shapes the diffusion of linguistic forms, yet direct experimental evidence remains limited. Across three laboratory experiments, we tested whether network structure or seed placement influences the spread of target lexical items, while holding ta...
Kerime Eylul Eski, L. Onnis· Cognitive Sciences· 0 citations
While the local clustering coefficient is central to network analysis, it is typically treated as a static property. We introduce delta clustering to quantify changes in an individual's local clustering across adjacent time points in undirected networks. To address structural constraints, we develop a density-based dec...
Cheng Wang, Omar Lizardo, David S. Hachen· Sociological Methods & R...· 0 citations
Evaluating network interventions requires understanding how treatment affects people through their social relationships. Counting treated neighbors without distinguishing supportive and antagonistic ties can conceal opposing influences. We define effects through positive and negative ties, their interaction, and a sign...
Xiao-Jing Du, Jiu-Yong Li, Lin Liu et al.· 0 citations
It is shown that the more people who share a common friend, the more connected that person tends to be, and an expression quantifying this progression is derived.
Alec M. McGail, Scott Feld· Proceedings of the National...· 0 citations