Micro-macro dynamics of the online opinion evolution: an asynchronous network model approach

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper investigates the complex relationship between endogenous and exogenous, deterministic and stochastic stimulating factors in public opinion dynamics. An asynchronous multi-agent network model is proposed to explore the interaction mechanism between individual opinions and the public opinion in online multi-agent network community, including both the micro and the macro patterns of opinion evolution. In addition, based on random network models, a novel algorithm is provided for opinion evolution prediction. The model property analysis and numerical experiments show that the proposed asynchronous multi-agent network model can assimilate and explain some interesting phenomena that are observed in the real world. Further case studies with numerical simulation and real-world applications confirm the feasibility and flexibility of the proposed model in public opinion analysis. The results challenge the common perception that mass media or opinion facilitators play the fundamental role in controlling the development trends of public opinion. This study shows that the formation and evolution of public opinion in the presence of opinion leaders depend also on an individual’s emotional inertia and conformity pressures from peers in the same topic group

The role of homophily in the emergence of opinion controversies

Understanding the emergence of strong controversial issues in modern societies is a key issue in opinion studies. A commonly diffused idea is the fact that the increasing of homophily in social networks, due to the modern ICT, can be a driving force for opinion polariation. In this paper we address the problem with a modelling approach following three basic steps. We first introduce a network morphogenesis model to reconstruct network structures where homophily can be tuned with a parameter. We show that as homophily increases the emergence of marked topological community structures in the networks raises. Secondly, we perform an opinion dynamics process on homophily dependent networks and we show that, contrary to the common idea, homophily helps consensus formation. Finally, we introduce a tunable external media pressure and we show that, actually, the combination of homophily and media makes the media effect less effective and leads to strongly polarized opinion clusters.Comment: 24 pages, 10 figure

Belief Dynamics in Social Networks: A Fluid-Based Analysis

The advent and proliferation of social media have led to the development of mathematical models describing the evolution of beliefs/opinions in an ecosystem composed of socially interacting users. The goal is to gain insights into collective dominant social beliefs and into the impact of different components of the system, such as users' interactions, while being able to predict users' opinions. Following this thread, in this paper we consider a fairly general dynamical model of social interactions, which captures all the main features exhibited by a social system. For such model, by embracing a mean-field approach, we derive a diffusion differential equation that represents asymptotic belief dynamics, as the number of users grows large. We then analyze the steady-state behavior as well as the time dependent (transient) behavior of the system. In particular, for the steady-state distribution, we obtain simple closed-form expressions for a relevant class of systems, while we propose efficient semi-analytical techniques in the most general cases. At last, we develop an efficient semi-analytical method to analyze the dynamics of the users' belief over time, which can be applied to a remarkably large class of systems.Comment: submitted to IEEE TNS

The Impact of Network Flows on Community Formation in Models of Opinion Dynamics

We study dynamics of opinion formation in a network of coupled agents. As the network evolves to a steady state, opinions of agents within the same community converge faster than those of other agents. This framework allows us to study how network topology and network flow, which mediates the transfer of opinions between agents, both affect the formation of communities. In traditional models of opinion dynamics, agents are coupled via conservative flows, which result in one-to-one opinion transfer. However, social interactions are often non-conservative, resulting in one-to-many transfer of opinions. We study opinion formation in networks using one-to-one and one-to-many interactions and show that they lead to different community structure within the same network.Comment: accepted for publication in The Journal of Mathematical Sociology. arXiv admin note: text overlap with arXiv:1201.238