Exploring the spiral of silence in adjustable social networks

Abstract

This study extends the understanding of the spiral of silence theory by taking into account four factors, including the topology of networks, the time factor of information transmission, the node degree of individuals and the freedom of expression. Simulation experiments analyze the silencers, public opinion in steady state and relaxation time in small-world networks, scale-free networks and community-structured networks by adjusting the initial conditions. Results highlight that individuals are easier to keep silent in scale-free network, especially when the individual with big degree and minority opinion starts the discussion. Conversely, there are only a few individuals keep silent in the community-structured network when the two communities hold opposite opinions. Moreover, the number of silencers grows as the degree of coupling increases, and it decreases as the freedom of expression goes up. By analyzing the public opinion evolution, we also find some important conditions, such as the network topology, the potential public opinion distribution, and the status and sides of the first speaker, can drive the minority reversal.

Noise-induced absorbing phase transition in a model of opinion formation

“…2 we exhibit the numerical results for O versus q and typical values of p, together with the analytical result given by Eq. (11). One can observe transitions at different points q c that depend on p, with the usual finite-size effects for p = 0.1, 0.2 and 0.3 (see the inset).…”

“…Even simple models can exhibit an interesting collective behavior that emerges from the microscopic interaction among individuals or agents in a given social network. Usually those models exhibit nonequilibrium phase transitions and rich critical phenomena, which justifies the interest of physicists in the study of opinion dynamics [1,2,3,4,5,6,7,8,9,10,11].…”

Are social bots a real threat? An agent-based model of the spiral of silence to analyse the impact of manipulative actors in social networks

“…(Nowak et al, 1990, p. 373) The call for more network-based research on opinion formation theories has been echoed but rarely answered (Song & Boomgaarden, 2017). In the context of the spiral of silence, researchers have used network models to examine the influence of longrange interactions (Jiang, Hua, Zhu, Wang, & Zhou, 2008), the influence of the chosen network topology (Wu, Du, Li, & Chen, 2015) or the influence of neutrals and hardcore nonconformists (Takeuchi, Tanaka, Fujie, & Suzuki, 2015) on opinion dynamics. However, to our knowledge, there have not been any simulation studies on the deliberate manipulation of public opinion in the context of the spiral of silence.…”

Opinion Expression Dynamics in Social Media Chat Groups: An Integrated Quasi-Experimental and Agent-Based Model Approach

“…For instance, the study assumed people who received external opinion pressure larger than peer support would be less likely to speak out to protect their opinion. As time progressed, the minority opinion would fall into silence in any kind of social network, especially when it was the Barabasi-Albert scale-free network [41]. Social bot studies also proposed that the spiral of silence theory would lead agents to consensus opinion in a social network, with some agents being silenced.…”