Exploring the Performance of Diffusion Models in Weighted Social Networks

In the present time, social networks have become a quintessential part of people's lives, by transforming how people connect and communicate. Social networks have become an important medium for information diffusion and social interactions. The rate of diffusion often depends upon network topology, influencing power of the initial adopters and the underlying node activation criteria. Most real-world social networks are weighted in nature, with edge weights representing the tie strength between the two connected nodes. In our research, we explore and analyze the performance of popular diffusion models in weighted social networks. The performance of 4 prevalent diffusion models, namely - Independent Cascade, Weighted Cascade, Trivalency and Linear Threshold, is compared with regards to the attained spread of information. The study was performed on 2 real-world weighted social networks.