Opinion dynamics in social networks with stubborn agents: An issue-based perspective

Abstract Classic models on opinion dynamics usually focus on a group of agents forming their opinions interactively over a single issue. Yet generally agreement cannot be achieved over a single issue when agents are not completely open to interpersonal influence. In this paper, opinion formation in social networks with stubborn agents is considered over issue sequences. The social network with stubborn agents is described by the Friedkin–Johnsen (F–J) model where agents are stubborn to their initial opinions. Firstly, we propose a sufficient and necessary condition in terms of network topology for convergence of the F–J model over a single issue. Secondly, opinion formation of the F–J model is investigated over issue sequences. Our analysis establishes connections between the interpersonal influence network and the network describing the relationship of agents’ initial opinions for successive issues. Taking advantage of these connections, we derive the sufficient and necessary condition for the F–J model to achieve opinion consensus and form clusters over issue sequences, respectively. Finally, we consider a more general scenario where each agent has bounded confidence in forming its initial opinion. By analyzing the evolution of agents’ ultimate opinions for each issue over issue sequences, we prove that the connectivity of the state-dependent network is preserved in this setting. Then the conditions for agents to achieve opinion consensus over issue sequences are established. Simulation examples are provided to illustrate the effectiveness of our theoretical results.

[1]  David Lee,et al.  Biased assimilation, homophily, and the dynamics of polarization , 2012, Proceedings of the National Academy of Sciences.

[2]  Jon M. Kleinberg,et al.  How bad is forming your own opinion? , 2015, Games Econ. Behav..

[3]  Long Wang,et al.  Aggregation of Foraging Swarms , 2004, Australian Conference on Artificial Intelligence.

[4]  Asuman E. Ozdaglar,et al.  Spread of (Mis)Information in Social Networks , 2009, Games Econ. Behav..

[5]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[6]  Matthew O. Jackson,et al.  Naïve Learning in Social Networks and the Wisdom of Crowds , 2010 .

[7]  D. Helbing,et al.  Leadership, consensus decision making and collective behaviour in humans , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[8]  John N. Tsitsiklis,et al.  On Krause's Multi-Agent Consensus Model With State-Dependent Connectivity , 2008, IEEE Transactions on Automatic Control.

[9]  Long Wang,et al.  Containment control of heterogeneous multi-agent systems , 2014, Int. J. Control.

[10]  Long Wang,et al.  Equilibrium topology of multi-agent systems with two leaders: A zero-sum game perspective , 2016, Autom..

[11]  Aparna Joshi,et al.  Unpacking Generational Identities in Organizations , 2010 .

[12]  Roberto Tempo,et al.  Novel Multidimensional Models of Opinion Dynamics in Social Networks , 2015, IEEE Transactions on Automatic Control.

[13]  M. Degroot Reaching a Consensus , 1974 .

[14]  Noah E. Friedkin,et al.  A Formal Theory of Reflected Appraisals in the Evolution of Power , 2011 .

[15]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[16]  M. Egidi,et al.  The emergence of path-dependent behaviors in cooperative contexts , 1997 .

[17]  D. North Institutions, Institutional Change and Economic Performance: Economic performance , 1990 .

[18]  Long Wang,et al.  Topology selection for multi-agent systems with opposite leaders , 2016, Syst. Control. Lett..

[19]  Long Wang,et al.  Consensus of switched multi-agent systems with random networks , 2017, Int. J. Control.

[20]  D. North Institutions, institutional change and economic performance: Cambridge university press. , 1990 .

[21]  Long Wang,et al.  Finite-Time Consensus Problems for Networks of Dynamic Agents , 2007, IEEE Transactions on Automatic Control.

[22]  Long Wang,et al.  Consensus of Hybrid Multi-Agent Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[23]  Guangming Xie,et al.  Controllability of multi-agent systems based on agreement protocols , 2009, Science in China Series F: Information Sciences.

[24]  Y.-Y. Liu,et al.  The fundamental advantages of temporal networks , 2016, Science.

[25]  Xiaoming Hu,et al.  Opinion consensus of modified Hegselmann-Krause models , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[26]  Richard A. Brualdi,et al.  Combinatorial matrix theory , 1991 .

[27]  Long Wang,et al.  Structural controllability of multi-agent systems with absolute protocol under fixed and switching topologies , 2016, Science China Information Sciences.

[28]  Randal W. Beard,et al.  Consensus seeking in multiagent systems under dynamically changing interaction topologies , 2005, IEEE Transactions on Automatic Control.

[29]  Chiara Ravazzi,et al.  Distributed randomized algorithms for opinion formation, centrality computation and power systems estimation: A tutorial overview , 2015, Eur. J. Control.

[30]  Jennifer Todd,et al.  IISSSSCC DD IISSCCUUSSSSIIOONN PP AAPPEERR SS EERRIIEESS T HE R OOTS OF I NTENSE E THNIC C ONFLICT MAY NOT IN FACT BE E THNIC :C ATEGORIES , C OMMUNITIES AND P ATH D EPENDENCE Joseph , 2017 .

[31]  Claudio Altafini,et al.  Consensus Problems on Networks With Antagonistic Interactions , 2013, IEEE Transactions on Automatic Control.

[32]  Francesco Bullo,et al.  Opinion Dynamics in Heterogeneous Networks: Convergence Conjectures and Theorems , 2011, SIAM J. Control. Optim..

[33]  Long Wang,et al.  Consensus of Multiagent Systems With Distance-Dependent Communication Networks , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[34]  Francesco Bullo,et al.  Opinion Dynamics and the Evolution of Social Power in Influence Networks , 2015, SIAM Rev..

[35]  Noah E. Friedkin,et al.  The Problem of Social Control and Coordination of Complex Systems in Sociology: A Look at the Community Cleavage Problem , 2015, IEEE Control Systems.

[36]  Francesco Bullo,et al.  On the reflected appraisals dynamics of influence networks with stubborn agents , 2014, 2014 American Control Conference.

[37]  I. Couzin,et al.  Effective leadership and decision-making in animal groups on the move , 2005, Nature.

[38]  Chiara Ravazzi,et al.  Ergodic Randomized Algorithms and Dynamics Over Networks , 2013, IEEE Transactions on Control of Network Systems.

[39]  Peter McKiernan,et al.  Strategy options and cognitive freezing: The case of the Dundee jute industry in Scotland , 2006 .

[40]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[41]  Long Wang,et al.  Asynchronous Consensus in Continuous-Time Multi-Agent Systems With Switching Topology and Time-Varying Delays , 2006, IEEE Transactions on Automatic Control.

[42]  Long Wang,et al.  A new approach to consensus problems in discrete-time multiagent systems with time-delays , 2006, 2006 American Control Conference.

[43]  R. Srikant,et al.  Opinion dynamics in social networks with stubborn agents: Equilibrium and convergence rate , 2014, Autom..

[44]  Rainer Hegselmann,et al.  Opinion dynamics and bounded confidence: models, analysis and simulation , 2002, J. Artif. Soc. Soc. Simul..

[45]  Leslie Lamport,et al.  The Byzantine Generals Problem , 1982, TOPL.

[46]  Guangming Xie,et al.  Necessary and sufficient conditions for containment control of networked multi-agent systems , 2012, Autom..

[47]  Gordon F. Royle,et al.  Algebraic Graph Theory , 2001, Graduate texts in mathematics.

[48]  J. Wolfowitz Products of indecomposable, aperiodic, stochastic matrices , 1963 .

[49]  Ananthram Swami,et al.  Consensus, Polarization and Clustering of Opinions in Social Networks , 2013, IEEE Journal on Selected Areas in Communications.

[50]  Stephen P. Boyd,et al.  Randomized gossip algorithms , 2006, IEEE Transactions on Information Theory.