I-SFI model of propagation dynamic based on user’s interest intensity and considering birth and death rate

Everyone has a different level of interest in a trending topic posted on social media, which may affect user’s behaviour. In order to find out the way it affects the process of information transmission, we construct an interest intensity-based susceptible-forwarding-immune$\left({I - SFI} \right)$I−SFI propagation dynamic model and two parameters birth rate$ A$A and death rate$ \mu $μ are introduced to represent the users who newly join the group of disseminated information and the users who leave this population. And we give different birth rates to people with various levels of interest, which helps us to determine the interest intensity of potential users to a certain extent. We use the forwarding data of the real topic on Chinese Sina-microblog for data fitting, which can accurately parameterize the model and quantify the impact of interest intensity. And sensitivity analyses also give some strategies for increasing the impact of information dissemination process from the perspective of interest intensity.