  Many empirical networks are intrinsically pluralistic, with interactions
occurring within groups of arbitrary agents. Then the agent in the network can
be influenced by types of neighbors, common examples include similarity,
opposition, and negligibility. Although the influence of neighbors can be
described as an amicable and antagonistic relationship in complex real-world
systems accurately, and the research on the dynamic process of public opinion
evolution with different types of influence is valuable, few studies have
mentioned that issue. In this paper, we develop a novel model on networks of
agents with the bi-directional bounded thresholds for studying the evolution of
opinion dynamics. We define the scope of individual assimilation and exclusion
to identify different types of neighbors and calculate the impact of the
corresponding neighbors on the individuals by converting the opinion
difference. The simulation results show that the proposed mechanism can
effectively explain the formation of bi-polarization during opinion evolution
and the settings of the bi-directional bounded thresholds significantly
influence the eventual distribution of opinions. Furthermore, we explore the
impacts of the initial conditions and the structure of the small-world network
on the evolution of opinions.
