Abstract
The existing opinion dynamics models mainly concentrate on the impact of opinions on other opinions and ignore the effect of the social similarity between individuals. Social similarity between an individual and their neighbors will also affect their opinions in real life. Therefore, an opinion evolution model considering social similarity (social-similarity-based HK model, SSHK model for short) is introduced in this paper. Social similarity is calculated using individual properties and is used to measure the social relationship between individuals. By considering the joint effect of confidence bounds and social similarity in this model, the role of neighbors’ selection is changed significantly in the process of the evolution of opinions. Numerical results demonstrate that the new model can not only obtain the salient features of the opinion result, namely, fragmentation, polarization, and consensus, but also achieve consensus more easily under the appropriate similarity threshold. In addition, the improved model with heterogeneous and homogeneous confidence bounds and similarity thresholds are also discussed. We found that the improved heterogeneous SSHK model could acquire opinion consensus results more easily than the homogeneous SSHK model and the classical models when the confidence bound was related to the similarity threshold. This finding provides a new way of thinking and a theoretical basis for the guidance of public opinion in real life.
Highlights
Over the past decades, opinion dynamics as a special type of complex human behavior has attracted a great deal of interest from researchers in different scientific fields [1]
In the Deffuant model, every agent can only communicate with one of his neighbors at each time step, whereas every agent can communicate with all his neighbors in the HK model, which serves to alter the present situation of the social network [16, 17]
This paper proposed an improved similarity-based Hegselmann–Krause model (SSHK) model based on a classical bounded confidence model by introducing social similarity between agents into the MHK model, simultaneously considering the influence of neighbors’ opinions and their social relationships as well
Summary
Opinion dynamics as a special type of complex human behavior has attracted a great deal of interest from researchers in different scientific fields [1]. Opinion dynamics, including opinion formation, spread, and evolution, has great influence on politics [2], economics [3], and society [4]. Existing studies have examined the inherent mechanism of the spread of opinion by establishing several opinion evolution models to forecast or influence public opinion [5]. In the existing study of opinion dynamics, models can be divided into discrete opinion models and continuous models [6, 7]. The most popular continuous opinion spreading models are the Deffuant model and the Hegselmann–Krause (HK) model [8,9,10], known as bounded confidence models In these models, the confidence bound ( known as opinion threshold or tolerance) is the main factor that influences opinion consensus and drives stabilization [11]. The aim of the present study is to determine how to make an opinion reach
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