Perception, Action and the Social Dynamics of the Variable Self

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Contemporary understanding of riots: classical crowd psychology, ideology and the social identity approach

This article explores the origins and ideology of classical crowd psychology, a body of theory reflected in contemporary popularised understandings such as of the 2011 English ‘riots’. This article argues that during the nineteenth century, the crowd came to symbolise a fear of ‘mass society’ and that ‘classical’ crowd psychology was a product of these fears. Classical crowd psychology pathologised, reified and decontextualised the crowd, offering the ruling elites a perceived opportunity to control it. We contend that classical theory misrepresents crowd psychology and survives in contemporary understanding because it is ideological. We conclude by discussing how classical theory has been supplanted in academic contexts by an identity-based crowd psychology that restores the meaning to crowd action, replaces it in its social context and in so doing transforms theoretical understanding of ‘riots’ and the nature of the self

Shared social identity transforms social relations in imaginary crowds

In this paper we present three studies that address the difference between physical and psychological groups, the conditions that create a transformation from the one into the other, and the psychological processes underlying this transformation. In Study 1 we demonstrate correlations between shared social identity, desired physical proximity to others, and positive emotions in the company of others. Study 2, employing a between-subjects design, finds that an event that creates shared fate, such as the breakdown of a train, leads to greater comfort in social interactions (e.g., ease of conversation) and comfort in sensual interactions (e.g., tolerance of physical touch) with other passengers, and that this occurs through an increase in shared social identity but not through social identification. Study 3 obtains similar findings using a within-subjects design. In combination, these studies provide consistent evidence for the role of shared social identity in the emergence of psychological groups from physical groups

From mindless masses to small groups: Conceptualizing collective behavior in crowd modeling.

Computer simulations are increasingly used to monitor and predict behavior at large crowd events, such as mass gatherings, festivals and evacuations. We critically examine the crowd modeling literature and call for future simulations of crowd behavior to be based more closely on findings from current social psychological research. A systematic review was conducted on the crowd modeling literature (N = 140 articles) to identify the assumptions about crowd behavior that modelers use in their simulations. Articles were coded according to the way in which crowd structure was modeled. It was found that 2 broad types are used: mass approaches and small group approaches. However, neither the mass nor the small group approaches can accurately simulate the large collective behavior that has been found in extensive empirical research on crowd events. We argue that to model crowd behavior realistically, simulations must use methods which allow crowd members to identify with each other, as suggested by self-categorization theory

Parsimony versus reductionism: how can crowd psychology be introduced into computer simulation?

Computer simulations are increasingly being used to predict the behaviour of crowds. However, the models used are mainly based on video observations, not an understanding of human decision making. Theories of crowd psychology can elucidate the factors underpinning collective behaviour in human crowds. Yet, in contrast to psychology, computer science must rely upon mathematical formulations in order to implement algorithms and keep models manageable. Here we address the problems and possible solutions encountered when incorporating social psychological theories of collective behaviour in computer modelling. We identify that one primary issue is retaining parsimony in a model whilst avoiding reductionism by excluding necessary aspects of crowd psychology, such as the behaviour of groups. We propose cognitive heuristics as a potential avenue to create a parsimonious model that incorporates core concepts of collective behaviour derived from empirical research in crowd psychology

Using social and behavioural science to support COVID-19 pandemic response

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behavior with the recommendations of epidemiologists and public health experts. Here we review experimental and correlational data from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic, and also highlight important gaps researchers should move quickly to fill in the coming weeks and months

A glossary for research on human crowd dynamics

This article presents a glossary of terms that are frequently used in research on human crowds. This topic is inherently multidisciplinary as it includes work in and across computer science, engineering, mathematics, physics, psychology and social science, for example. We do not view the glossary presented here as a collection of finalised and formal definitions. Instead, we suggest it is a snapshot of current views and the starting point of an ongoing process that we hope will be useful in providing some guidance on the use of terminology to develop a mutual understanding across disciplines. The glossary was developed collaboratively during a multidisciplinary meeting. We deliberately allow several definitions of terms, to reflect the confluence of disciplines in the field. This also reflects the fact not all contributors necessarily agree with all definitions in this glossary