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

The Natural Statistics of Audiovisual Speech

Humans, like other animals, are exposed to a continuous stream of signals, which are dynamic, multimodal, extended, and time varying in nature. This complex input space must be transduced and sampled by our sensory systems and transmitted to the brain where it can guide the selection of appropriate actions. To simplify this process, it's been suggested that the brain exploits statistical regularities in the stimulus space. Tests of this idea have largely been confined to unimodal signals and natural scenes. One important class of multisensory signals for which a quantitative input space characterization is unavailable is human speech. We do not understand what signals our brain has to actively piece together from an audiovisual speech stream to arrive at a percept versus what is already embedded in the signal structure of the stream itself. In essence, we do not have a clear understanding of the natural statistics of audiovisual speech. In the present study, we identified the following major statistical features of audiovisual speech. First, we observed robust correlations and close temporal correspondence between the area of the mouth opening and the acoustic envelope. Second, we found the strongest correlation between the area of the mouth opening and vocal tract resonances. Third, we observed that both area of the mouth opening and the voice envelope are temporally modulated in the 2–7 Hz frequency range. Finally, we show that the timing of mouth movements relative to the onset of the voice is consistently between 100 and 300 ms. We interpret these data in the context of recent neural theories of speech which suggest that speech communication is a reciprocally coupled, multisensory event, whereby the outputs of the signaler are matched to the neural processes of the receiver

Audio-visual speech scene analysis: Characterization of the dynamics of unbinding and rebinding the McGurk effect

International audienceWhile audiovisual interactions in speech perception have long been considered as automatic, recentdata suggest that this is not the case. In a previous study, Nahorna et al. [(2012). J. Acoust. Soc.Am. 132, 1061–1077] showed that the McGurk effect is reduced by a previous incoherentaudiovisual context. This was interpreted as showing the existence of an audiovisual binding stagecontrolling the fusion process. Incoherence would produce unbinding and decrease the weight ofthe visual input in fusion. The present paper explores the audiovisual binding system to characterizeits dynamics. A first experiment assesses the dynamics of unbinding, and shows that it is rapid: Anincoherent context less than 0.5 s long (typically one syllable) suffices to produce a maximalreduction in the McGurk effect. A second experiment tests the rebinding process, by presenting ashort period of either coherent material or silence after the incoherent unbinding context.Coherence provides rebinding, with a recovery of the McGurk effect, while silence providesno rebinding and hence freezes the unbinding process. These experiments are interpreted in theframework of an audiovisual speech scene analysis process assessing the perceptual organization ofan audiovisual speech input before decision takes place at a higher processing stage

Recent Advances in Opinion Modeling: Control and Social Influence

We survey some recent developments on the mathematical modeling of opinion dynamics. After an introduction on opinion modeling through interacting multi-agent systems described by partial differential equations of kinetic type, we focus our attention on two major advancements: optimal control of opinion formation and influence of additional social aspects, like conviction and number of connections in social networks, which modify the agents’ role in the opinion exchange process