Collaborative Diffusion Based on Value Measurement in Social–Physical Networks

In the study of information diffusion in social–physical networks, existing works are usually based on information entropy. These works measure and represent the information attribute characteristics independently for social networks and physical networks, resulting in ineffective interactions and waste of resources. Therefore, to solve the key problem of the mismatch between interaction demands and communication resources, the framework of collaborative diffusion based on value measurement is proposed in social–physical networks, including social–physical interaction, cognitive difference, and mutual trust degree of nodes. Based on parameterizing the relative strength of these influences by confidence and collaborative conservation factors, the collaborative diffusion model based on value measurement is established. Extensive simulations verify the influence of value measurement on the collaboration diffusion process, presented by the evolutions of value entropy, sentiment fragmentation, and diffusion range. In addition, the influence of collaboration on information dissemination is confirmed by the comparison of the change of value entropy and diffusion range. These results can help decision makers better balance the matching problem between interaction demands and available resources, which is beneficial to realize customized information diffusion.