Multivariate opinion evolution analysis on individual opinion differences: An agent-based model

The spiral of silence is a classic theory originating from the age of mass media, which posits that individuals may suppress dissenting opinions to avoid social exclusion. In the digital era, despite the persistence of this phenomenon, the rise of social media has catalyzed the emergence of an antispiral of silence-a counterphenomenon fueled by growing self-awareness and online anonymity. In this paper, we focus on an interesting phenomenon: how these two spirals compete with each other to promote pluralism in social networks. To this end, we propose the spiral competition model (SCM) to quantify the two spirals and explore the impact of this phenomenon on the evolution of public opinion. In the SCM, agents can generate pseudo-opinions as well as antiopinions. In addition, we propose a time-varying network topology updating algorithm based on triangle closure, which simulates the fluid nature of social connections. Furthermore, we propose a community-based opinion initialization method with Gaussian distribution for enhancing simulation fidelity. Finally, we applied complex network theory to information dissemination, and the model was then simulated and analyzed in Erdős-Rényi random networks. And the rationality of SCM was verified using Sina Weibo data. The experimental results show that while the spiral of silence initially holds sway, the antispiral of silence can precipitate significant opinion divergence during critical junctures, challenging the status quo. And if the antispiral of silence fails to prevail, the trend of public opinion will be difficult to reverse. This research helps us recognize the influence that can be brought about by the awakening of individual consciousness, and provides an important reference for public opinion prediction.