Summary: A new study examines how behaviors and ideas travel through social networks and finds that long ties—connections that bridge distant parts of a network—can dramatically speed up and broaden adoption. These long ties overcome the commonly held view that tightly clustered groups are always best for spreading complex behaviors, showing instead that even a small chance of adoption combined with randomly created long ties can produce widespread contagion.
Using rigorous mathematical and statistical analysis on network models, the research team explored the dynamics of noisy threshold-based contagions on circular lattices with randomly rewired edges. Their results show that when networks include long ties, the spread of new norms, products, or behaviors becomes faster and reaches more diverse communities than would be expected from local, tightly knit clusters alone. The findings have clear relevance for social behavior, public-health campaigns, marketing strategies, and even the study of neural activity.
Key Facts:
- Long ties—edges that connect distant nodes in a network—enable faster, wider diffusion of behaviors than local clustering alone.
- The study applied mathematical and simulation methods to show that a small probability of adoption below the usual threshold is sufficient for long ties to accelerate contagion.
- These network dynamics echo similar patterns observed in neural systems, suggesting a broader relevance beyond social networks.
Source: University of Pittsburgh
Social influence shapes many everyday decisions. From choosing a neighborhood shop to deciding whether to vaccinate a child, people frequently look to others in their social networks when forming opinions and making choices. Social contagion—the way behaviors, beliefs, or practices spread through connected individuals—helps explain how new norms and products gain traction.
“People tend to form networks—both online and offline—that reflect similar perspectives,” explained Amin Rahimian, assistant professor of industrial engineering at the University of Pittsburgh Swanson School of Engineering. “Understanding social contagion in networks helps explain how and why new norms, products, and ideas spread.”
Earlier work emphasized the role of close-knit, highly clustered ties in spreading complex behaviors that require social reinforcement. By contrast, this study—conducted by Rahimian together with researchers from MIT and Harvard—demonstrates that introducing long ties through random rewiring accelerates adoption across a network. In modern contexts such as social media, long ties allow information to jump across communities, reaching individuals who would not be exposed via only local connections.
Through analysis of circular lattice models with rewired edges, the team showed that even when the probability of adopting a behavior is below the conventional contagion threshold, the presence of some long ties makes rapid, widespread diffusion possible. In other words, random long-range connections can compensate for low per-contact adoption probabilities and trigger cascades that would otherwise stall in localized clusters.
“The mechanisms we identify on circular lattices also extend to higher-dimensional network structures,” Rahimian noted, indicating that these insights are robust to changes in network geometry and scale.
The study’s implications reach beyond social systems. Similar patterns of spread appear in studies of neural activity, where bursts of activation propagate across brain regions. “We are interested in how these results improve our understanding of network structures that facilitate spreading or bursting activity in different brain areas,” said Jonathan Rubin, professor in Pitt’s Department of Mathematics.
From a practical standpoint, the research suggests that efforts aiming for rapid, near-complete diffusion should consider creating or leveraging long-tie connections that link distinct neighborhoods within a network. Strategic seeding of behaviors or messaging at points that bridge communities can accelerate adoption more efficiently than focusing only on dense local clusters, according to Dean Eckles, associate professor of marketing at MIT. He noted that future work could explore optimal seeding strategies for complex behaviors in networks that include long ties.
About this social neuroscience research news
Author: Paul Kovach
Source: University of Pittsburgh
Contact: Paul Kovach – University of Pittsburgh
Image: The image is credited to Neuroscience News
Original Research: Closed access. “Long ties accelerate noisy threshold-based contagions” by Amin Rahimian et al., published in Nature Human Behavior.
Abstract
Long ties accelerate noisy threshold-based contagions
Many widely used models of biological and social contagion show that randomly rewiring some edges—effectively creating longer-range connections—tends to accelerate spread. However, previous arguments have suggested that highly clustered networks can better facilitate threshold-based contagions, which model adoption decisions based on the behavior of neighbors and strategic complements. This study shows that small, realistic modifications to threshold-based contagion models change that conclusion.
By analyzing the rate of spread over circular lattices with rewired edges, the researchers demonstrate that allowing a modest probability of adoption below the traditional threshold is sufficient for random rewiring to accelerate noisy threshold-based contagions. The conclusion holds across simulations on empirical networks, persists under partial but sufficiently frequent rewiring, and remains valid when adoption is reversible though only rarely so. The results also extend to higher-dimensional lattice structures, harmonizing theoretical insights about how network topology influences diffusion.