Opinion Dynamics: Models, Extensions and External Effects

Abstract

Recently, social phenomena have received a lot of attention not only from social scientists, but also from physicists, mathematicians and computer scientists, in the emerging interdisciplinary field of complex system science. Opinion dynamics is one of the processes studied, since opinions are the drivers of human behaviour, and play a crucial role in many global challenges that our complex world and societies are facing: global financial crises, global pandemics, growth of cities, urbanisation and migration patterns, and last but not least important, climate change and environmental sustainability and protection. Opinion formation is a complex process affected by the interplay of different elements, including the individual predisposition, the influence of positive and negative peer interaction (social networks playing a crucial role in this respect), the information each individual is exposed to, and many others. Several models inspired from those in use in physics have been developed to encompass many of these elements, and to allow for the identification of the mechanisms involved in the opinion formation process and the understanding of their role, with the practical aim of simulating opinion formation and spreading under various conditions. These modelling schemes range from binary simple models such as the voter model, to multi-dimensional continuous approaches. Here, we provide a review of recent methods, focusing on models employing both peer interaction and external information, and emphasising the role that less studied mechanisms, such as disagreement, has in driving the opinion dynamics. Due to the important role that external information (mainly in the form of mass media broadcast) can have in enhancing awareness of social issues, a special emphasis will be devoted to study different forms it can take, investigating their effectiveness in driving the opinion formation at the population level. The review shows that, although a large number of approaches exist, some mechanisms such as the effect of multiple external information sources could largely benefit from further studies. Additionally, model validation with real data, which are starting to become available, is still largely lacking and should in our opinion be the main ambition of future investigations

Nonlinear societal change: The perspective of dynamical systems

“…Our model emphasizes the well-documented tendency for people to adopt the ideas, beliefs, and conclusions voiced by others who are physically or psychologically close (e.g., Asch, 1956;Bond & Smith, 1996;Burnstein & Vinokur, 1977;Christakis & Fowler, 2009;Doise, 1969;Festinger, 1950;Heider, 1958;Myers, 1982;Newcomb, 1952;de Oca et al, 2011;Schachter, 1951;Sîrbu et al, 2016). This tendency is enhanced under conditions of ambiguity that allow for wide latitude in the interpretation of events and issues (e.g., Deutsch & Gerard, 1955;Diener, 1980;Kruglanski & Webster, 1996;Sherif, 1936;Simon & Holyoak, 2002) or when the event or issue in question is personally important (e.g., Crano, 2012;Hogg, 2015;Janis, 1972;Latan e, 1981;MacCoun, 2012;Moscovici & Zavalloni, 1969).…”

“…The individual's own position (i.e., self‐influence ) is taken into account as well and is given the same weight as his or her nearest neighbour. The individual adopts the opinion that is most prevalent in each round of interaction, a rule that is consistent with research on social influence (e.g., Abrams, Wetherell, Cochrane, Hogg, & Turner, ; Asch, ; Festinger, Schachter, & Back, ; Schachter, ) and that is most often adopted in models of opinion dynamics (e.g., de Oca et al ., ; Sîrbu, Loreto, Servedio, & Tria, ). In computational terms, the strength of influence of each opinion is described in terms of the formula described above.…”

(CMMSE paper) A finite‐difference model for indoctrination dynamics

“…Recently, a great interest has arisen in the study of social phenomena using the models and tools from complex systems science, statistical physics, and quantum field theory . Among these social phenomena, the opinion dynamics has become an important field by itself . Opinions can be interpreted as assessments made by the agents about prices, levels of preference (or agreement) with political parties, or controversial topics.…”

Emergência de distribuições de posicionamentos ideológicos: uma abordagem computacional

“…. O modelo Sznajd tambéḿ e bastante discutido na literaturaSZNAJD, 2000;SÎRBU et al, 2017;CASTELLANO, 2012). Em sua versão original, e mais simples, os agentes estão localizados em uma grade unidimensional.…”

“…Não por acaso, ABMs são amplamente usados em OD (CASTELLANO, 2012; FLACHE et al, 2017).Que elementos constituem os modelos de OD? Podemos delimitar um modelo de dinâmicas de opinião da seguinte forma: agentes conectados possuem opiniões como variáveis e interagem segundo regras que explicam a mudança ou manutenção das opiniões individuais sob efeito da interação com outros agentes ou outras fontes (como a mídia)(SÎRBU et al, 2017). Os agentes num modelo em OD têm então uma opinião, uma estrutura de interação e uma regra de atualização de sua opinião.…”