Phase transitions in the q-voter model with two types of stochastic driving

In this paper we study nonlinear $q$-voter model with stochastic driving on a complete graph. We investigate two types of stochasticity that, using the language of social sciences, can be interpreted as different kinds of nonconformity. From a social point of view, it is very important to distinguish between two types nonconformity, so called anti-conformity and independence. A majority of works suggests that these social differences may be completely irrelevant in terms of microscopic modeling that uses tools of statistical physics and that both types of nonconformity play the role of so called 'social temperature'. In this paper we clarify the concept of 'social temperature' and show that different type of 'noise' may lead to qualitatively different emergent properties. In particularly, we show that in the model with anti-conformity the critical value of noise increases with parameter $q$, whereas in the model with independence the critical value of noise decreases with the $q$. Moreover, in the model with anti-conformity the phase transition is continuous for any value of $q$, whereas in the model with independence the transition is continuous for $q \le 5$ and discontinuous for $q>5$

Opinion dynamics: models, extensions and external effects

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. [...]Comment: 42 pages, 6 figure

Dynamic network approach to marriage/divorces problem

We extend "stable marriage problem" studied via computer simulation (agent-based) from network perspective by dynamical generalization. We investigate how preferential or random attachment of individuals can affect simulation results such as: proportion of singles in society, number of divorces etc. We took into account attractiveness of individuals and its different types as well as personal taste. Current value of socio-economic pressure p (main model parameter) drives the dynamic of first marriage, remarriage or spontaneously marriage breaks up. Model reflects the behavior of the simplified heterosexual population (frequency of changing partners, the ratio of singles in society). Theoretical agent-based simulation (with populational approaches, e.g. Births and deaths) should be later supplemented by historical values of divorces/marriages in different countries of the world. Stable (constant) society was also implemented to show difference with "living" society. In this model, agents have attribute of attraction. Preferential attachment, known from network theory, was introduced, to mimic selection process. Additionally, totally random attachment (not attraction-depended) was also implemented for contrast

Is It Necessary to Lie to Win a Controversial Public Debate?:An Answer from Sociophysics

Controversial public debates driven by incomplete scientific data where nobody can claim absolute certainty, due to the current state of scientific knowledge, are studied. To adopt a cautious balanced attitude based on clear but inconclusive data appears to be a lose-out strategy. In contrast overstating arguments with incorrect claims which cannot be scientifically refuted appears to be necessary but not sufficient to eventually win a public debate. The underlying key mechanisms of these puzzling and unfortunate conclusions are identified using the Galam Unifying Frame (GUF) of opinion dynamics. It reveals that the existence of inflexible agents and their respective proportions are the instrumental parameters to determine the faith of incomplete scientific data in public debates. Acting on one’s own inflexible proportion modifies the topology of the flow diagram, which in turn can make irrelevant the value of initial support. On the contrary focusing on open-minded agents may be useless given some topologies. Accordingly, the inflexibles rather than the data are found to drive the opinion of the population. The results shed a new but disturbing light on designing adequate strategies to win a public debate. The cases of global warming is briefly discussed