The dynamics of audience applause

The study of social identity and crowd psychology looks at how and why individual people change their behaviour in response to others. Within a group, a new behaviour can emerge first in a few individuals before it spreads rapidly to all other members. A number of mathematical models have been hypothesized to describe these social contagion phenomena, but these models remain largely untested against empirical data. We used Bayesian model selection to test between various hypotheses about the spread of a simple social behaviour, applause after an academic presentation. Individuals' probability of starting clapping increased in proportion to the number of other audience members already ‘infected’ by this social contagion, regardless of their spatial proximity. The cessation of applause is similarly socially mediated, but is to a lesser degree controlled by the reluctance of individuals to clap too many times. We also found consistent differences between individuals in their willingness to start and stop clapping. The social contagion model arising from our analysis predicts that the time the audience spends clapping can vary considerably, even in the absence of any differences in the quality of the presentations they have heard

Collective animal behaviour in moving groups

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Collective animal behaviour in moving groups

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Navigation in human crowds; testing the many-wrongs principle

The 'many-wrongs principle' predicts that animal group cohesion can cause groups to navigate more accurately than singletons. Recent theoretical work using individual-based simulations and several empirical studies of bird flock behaviour support this principle. However, for real animal groups it remains unclear what key factors are involved and whether group cohesion alone can act to produce the effect. We tested model predictions using human participants in a large circular arena. They were tested alone and in groups of two, three, six and 10, in three trials. For each trial, individuals were instructed to stay together and approach a preset but unmarked target on the arena perimeter. The target instruction included a degree of directional uncertainty of 22.5°, 67.5° or 112.5°. Individual directional uncertainty was equal for each group member within a trial, but differed between trials. As expected, we found that groups comprising individuals with lower directional uncertainty navigated more accurately. Group navigational accuracy increased with group size but only between singletons and groups of 10 and only when individuals had a high directional uncertainty of 112.5°. This study provides evidence in human groups that group cohesion can increase navigational accuracy but that this effect is restricted to larger group sizes and when individual directional uncertainty is high. © 2009 The Association for the Study of Animal Behaviour

Emergent Sensing of Complex Environments by Mobile Animal Groups

The capacity for groups to exhibit collective intelligence is an often-cited advantage of group living. Previous studies have shown that social organisms frequently benefit from pooling imperfect individual estimates. However, in principle, collective intelligence may also emerge from interactions between individuals, rather than from the enhancement of personal estimates. Here, we reveal that this emergent problem solving is the predominant mechanism by which a mobile animal group responds to complex environmental gradients. Robust collective sensing arises at the group level from individuals modulating their speed in response to local, scalar, measurements of light and through social interaction with others. This distributed sensing requires only rudimentary cognition and thus could be widespread across biological taxa, in addition to being appropriate and cost-effective for robotic agents

How perceived threat increases synchronization in collectively moving animal groups

Nature is rich with many different examples of the cohesive motion of animals. Previous attempts to model collective motion have primarily focused on group behaviours of identical individuals. In contrast, we put our emphasis on modelling the contributions of different individual-level characteristics within such groups by using stochastic asynchronous updating of individual positions and orientations. Our model predicts that higher updating frequency, which we relate to perceived threat, leads to more synchronized group movement, with speed and nearest-neighbour distributions becoming more uniform. Experiments with three-spined sticklebacks (Gasterosteus aculeatus) that were exposed to different threat levels provide strong empirical support for our predictions. Our results suggest that the behaviour of fish (at different states of agitation) can be explained by a single parameter in our model: the updating frequency. We postulate a mechanism for collective behavioural changes in different environment-induced contexts, and explain our findings with reference to confusion and oddity effects

Mechanisms of group decisions.

<p>Shown are the different categories of how groups decided on a word based on the collection of independent responses/words. Consensus: all independent responses were identical to the group response; majority: the group response corresponded to the word that was most often reconstructed during the independent responses; tie: the group response corresponded to one of two (or more) words that were most often reconstructed during the independent responses; minority: the group response was present in the independent responses but was not one of the words that were most often given in the independent responses; invented: the group response was not present in the independent responses. Per category, the frequency (labelled as “N”) and the success rate (mean ± SE) of individuals (white bars) and groups (dark bars) are shown. Whenever an individual did not fill in a word as an independent response this was considered as ‘incorrect’. Majority decisions resulted in higher success rate and were much more frequent than minority decisions, which did not improve success rate. </p