Abstract:
Research related to information diffusion within complex networks tends to focus on the effective ways to maximize its reach and dynamics. Most of the strategies are base...Show MoreMetadata
Abstract:
Research related to information diffusion within complex networks tends to focus on the effective ways to maximize its reach and dynamics. Most of the strategies are based on seeding nodes according to their potential role for social influence. The presented study shows how the seeding can be supported by changes in the target users' motivation to spread the content, thus modifying the propagation probabilities. The allocation of propagation probabilities to nodes takes the form of a spraying process following a given probability distribution, projected from the nodes' rankings. The results showed how different spraying strategies affect the results when compared to the commonly used uniform distribution. Apart from the performance analysis, the empirical study shows to which extent the seeding of nodes with high centrality measures can be compensated by seeding the nodes which are ranked lower, but are having higher motivation and propagation probabilities.
Published in: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Date of Conference: 28-31 August 2018
Date Added to IEEE Xplore: 25 October 2018
ISBN Information: