Gossip on Weighted Networks

We investigate how suitable a weighted network is for gossip spreading. The proposed model is based on the gossip spreading model introduced by Lind et.al. on unweighted networks. Weight represents “friendship.” Potential spreader prefers not to spread if the victim of gossip is a “close friend”. Gossip spreading is related to the triangles and cascades of triangles. It gives more insight about the structure of a network. We analyze gossip spreading on real weighted networks of human interactions. 6 co-occurrence and 7 social pattern networks are investigated. Gossip propagation is found to be a good parameter to distinguish co-occurrence and social pattern networks. As a comparison some miscellaneous networks and computer generated networks based on ER, BA, WS models are also investigated. They are found to be quite different than the human interaction networks.

💡 Research Summary

The paper extends the classic gossip‑spreading model, originally defined on unweighted graphs, to weighted networks where each edge carries a numerical “friendship” strength. The authors argue that in real human interactions the likelihood of transmitting gossip depends not only on the existence of a tie but also on how close the two individuals are: the closer the relationship, the less likely a person will spread negative information about a close friend. To capture this intuition, they introduce a weight‑dependent transmission rule. An edge weight w∈