Information spreading in complex networks based on population characteristics

To control information spreading in different populations effectively, an information spreading model was built considering population characteristics and the simulation experiments were conducted in different networks to study the influence of network topology, social reinforcement and population characteristics on information spreading. The results show that the homophyly of population characteristics is more beneficial to information spreading. Information spreads wider in small-world network and faster in scale-free network in the early process. Larger spreading scale comes with stronger social reinforcement. This tendency is more obvious in heterogeneous population. The results will be of a certain reference value in information spreading management.