title: Modeling of information diffusion in Twitter-like social networks under information overload.
abstract: Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations.
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China.
authors.forename: Pei
authors.identifier: 0000-0001-8699-8825
authors.initials: P
authors.lastname: Li
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China.
authors.forename: Hui
authors.identifier: 0000-0003-4807-6680
authors.initials: H
authors.lastname: Wang
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China.
authors.forename: Xin
authors.identifier: 0000-0003-2954-2076
authors.initials: X
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D003142:Communication; D006801:Humans; D020407:Internet; D008962:Models, Theoretical