Modelling the Emergent Behaviour of Human Social Groups

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Military / Coalition Issue

Coalition operations require the ability to understand, predict and adapt to the behaviours of complex social situations involving sets of interacting actors and individuals; in which the behaviour of groups emerges from the psychological behaviours of individuals. This is wide-ranging, from disaster relief, to extremists, to conflict and to adversarial online activities as seen through dis-information campaigns.

Core idea and Key Achievements

The research has established ways in which agents in computerised “agent-based models” can be embedded with individual psychological behaviours. Then “multi-agent models” are used to extend the psychological behaviours to groups, resulting in the evolution of collective effects that define how group behaviours emerge. This provides insight into the factors which impact the cultural spread of particular behaviours, including negative social behaviours such as hate, and the way in which human groups form, sustain and evolve. The research has focused on i) prejudice, ii) identity, and iii) cognitive dissonance.

Implications for Defence

The “multi-agent models” make it possible to explore particular scenarios of how groups may evolve. This can aide training, planning, and wider understanding of how human psychology, at the individual level, can influence the collective behaviour and evolution of groups, such as under stress or cultural distrust. Further, it provides insight into the interactions motivating behavioural responses in individuals such as devotion to a cause.

Readiness and Alternative Defence Uses

The research has established the concepts and capabilities at a fundamental level, resulting in two Nature publications (Scientific Reports) and a further pending IEEE transactions publication. This represents low technology readiness level (TRL) research. However, there is substantial potential to translate this into online social networks (e.g., the detection of strength of identity fusion for online analysis of social media interactions) to address, for example, scenarios concerned with identity fusion and devotion to a cause.

Resources and References

• Whitaker, Roger M., Gualtiero B. Colombo, and David G. Rand. “Indirect reciprocity and the evolution of prejudicial groups.” Scientific reports 8, no. 1 (2018): 1-14.
• Whitaker, R. M., Colombo, G. B., & Dunham, Y (2021). The evolution of strongly-held group identities, through agent-based cooperation Scientific reports, 11(1), 1-16.
• Whitaker, R. M., Colombo, G. B., Turner, L., Dunham, Y., Doyle, D., Roy, E.M., Giammanco, C.A., (2021), The Coevolution of Social Networks and Cognitive Dissonance. IEEE Transactions on Computational Social Systems,Accepted for publication.
• Whitaker, Roger M., Diane Felmlee, Dinesh C. Verma, Alun Preece, and Grace-Rose Williams. “From evolution to revolution: understanding mutability in large and disruptive human groups.” In Next-Generation Analyst V, vol. 10207, p. 1020703. International Society for Optics and Photonics, 2017.
• Whitaker, Roger M., Liam Turner, Gualtiero Colombo, Dinesh Verma, Diane Felmlee, and Gavin Pearson. “Intra-group tension under inter-group conflict: a generative model using group social norms and identity.” In International Conference on Applied Human Factors and Ergonomics, pp. 167-179. Springer, Cham, 2017.

Organisations

Cardiff, Penn State, Yale, ARL, Dstl, IBM