Journal of Statistical Physics

, Volume 151, Issue 1–2, pp 218–237 | Cite as

Opinion Dynamics with Disagreement and Modulated Information

  • Alina Sîrbu
  • Vittorio Loreto
  • Vito D. P. Servedio
  • Francesca Tria


Opinion dynamics concerns social processes through which populations or groups of individuals agree or disagree on specific issues. As such, modelling opinion dynamics represents an important research area that has been progressively acquiring relevance in many different domains. Existing approaches have mostly represented opinions through discrete binary or continuous variables by exploring a whole panoply of cases: e.g. independence, noise, external effects, multiple issues. In most of these cases the crucial ingredient is an attractive dynamics through which similar or similar enough agents get closer. Only rarely the possibility of explicit disagreement has been taken into account (i.e., the possibility for a repulsive interaction among individuals’ opinions), and mostly for discrete or 1-dimensional opinions, through the introduction of additional model parameters. Here we introduce a new model of opinion formation, which focuses on the interplay between the possibility of explicit disagreement, modulated in a self-consistent way by the existing opinions’ overlaps between the interacting individuals, and the effect of external information on the system. Opinions are modelled as a vector of continuous variables related to multiple possible choices for an issue. Information can be modulated to account for promoting multiple possible choices. Numerical results show that extreme information results in segregation and has a limited effect on the population, while milder messages have better success and a cohesion effect. Additionally, the initial condition plays an important role, with the population forming one or multiple clusters based on the initial average similarity between individuals, with a transition point depending on the number of opinion choices.


Opinion dynamics Interaction Disagreement External information Numerical simulations 



This research has been supported by the EveryAware project funded by the Future and Emerging Technologies program (IST-FET) of the European Commission under the EU RD contract IST-265432 and the EuroUnderstanding Collaborative Research Projects DRUST funded by the European Science Foundation.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Alina Sîrbu
    • 1
  • Vittorio Loreto
    • 1
    • 2
  • Vito D. P. Servedio
    • 2
  • Francesca Tria
    • 1
  1. 1.ISI FoundationTurinItaly
  2. 2.Physics Dept.Sapienza University of RomeRomeItaly

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