AI Article Synopsis
- The study examines how social contagion behaves on weighted networks, which are networks where connections between nodes have different strengths.
- It reveals that the uneven distribution of connections (degree heterogeneity) can change the way contagion spreads, and its effect on the total number of people adopting something varies based on transmission probabilities.
- Additionally, the research concludes that while the variation in connection weights always makes it harder for social contagion to spread, it does not change the type of transition in contagion dynamics.
Article Abstract
We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity cannot only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that the heterogeneity of weight distribution always hinders social contagions, and does not alter the transition type.
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| http://dx.doi.org/10.1103/PhysRevE.96.012306 | DOI Listing |
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