Intra-group Tension Under Inter-group Conflict: A Generative Model Using Group Social Norms and Identity

Whitaker, Roger M.; Turner, Liam D.; Colombo, Gualtiero B.; Verma, Dinesh; Felmlee, Diane; Pearson, Gavin

doi:10.1007/978-3-319-60747-4_16

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…In earlier research we explored event driven models for the evolution of group behavior. 21 This modeling approach involves actions taken in response to a social dilemma, based on individual and group-derived strategies. The social dilemma tests the extent of positivity or negativity towards a third party in the presence of interaction opportunities with others.…”

Section: Motifs and Emergence Of Inter-group Behaviormentioning

confidence: 99%

The role of motifs in understanding behavior in social and engineered networks

Braines

Felmlee

Towsley

et al. 2018

Next-Generation Analyst VI

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Within networks one can identify motifs that are significant recurring patterns of interaction between nodes. Here motifs are sub-graphs that occur more frequently than would be explained by random connections. Graphs can be used to model internal network structures of human groups, or links between groups, with group dynamics being governed by these structures. Graphs can also model behavior in engineered systems, and internal network structures can significantly affect dynamic behavior. A graph may only be partially visible (such as in hostile or coalition environments), however detectable network motifs may in some cases be reflective of the entire graph. We outline a research plan and describe basic network motifs and their properties, along with current analytic techniques for static and dynamic settings. We offer suggestions as to how network motif techniques can be applied to intra-or inter-group behavior, for example to detect whether multiple groups behave as a cooperative alliance, or whether coalition networks inter-operate in positive ways. As an example, we examine a complex time-series graph dataset relevant to coalition focused aspects of the class of networks under study, specifically related to the social network resulting from the authorship of academic papers within a coalition. We provide details of the basic analysis of this network over time and outline how this can be used as one of the datasets for our planned network motif research activities, especially with regards to the temporal and evolutionary aspects.

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Section: Motifs and Emergence Of Inter-group Behaviormentioning

confidence: 99%

The role of motifs in understanding behavior in social and engineered networks

Braines

Felmlee

Towsley

et al. 2018

Next-Generation Analyst VI

Self Cite

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“…The effect of different phenomena on group behavior and dynamics, across individual to group scales, has been the subject of much mathematical study since the 1940's [5] which has typically employed methods from physics and game theory. The physics-inspired approaches provide insight mainly through simulation (e.g., [6], [7]), and involve many parameters, while the game theoretic models ei-ther directly focus on simple two-player ultimatum and prisoner's dilemma games [8], [9], [10], [11], [12], or bespoke games relevant to particular scenarios (e.g., group conflict [13], [14], [15]). In the intervening time, many micro-economic models have been developed to describe specific group-dependent actions [16], [17], [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Mathematical models for social group behavior

Eshghi

Williams

Colombo

et al. 2017

2017 IEEE SmartWorld, Ubiquitous Intelligence &Amp; Computing, Advanced &Amp; Trusted Computed, Scalable Computing &Amp; Commun

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In this paper, we seek to identity how mathematical and economic analysis can be used to gain insights about the mutation of social groups. Group mutability has been studied in multiple domains, with insights generated on significant factors at differing scales. Mathematical modeling enables the simultaneous study of such phenomena, understanding interactions and generating hypotheses for experiments. In particular, we focus on group fracture, where individuals leave groups of which they are members. For example, this can be due to perceived differences with other group members due to norm related conflict (such as extreme actions by some members). Our aim is to consider simple mathematical models incorporating a selection of social and psychological theory which describes these phenomena as a way to understand their interplay, and describe the trade-offs and challenges. This will help a federation model the behavior of extremist groups, and determine not only when an intervention is necessary, but also the best course of action to take to induce the fracture of such groups. This paper is an exploratory investigation into methods of achieving this goal and evaluating the usefulness of the outputs to federations.

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“…A major concern in asymmetric warfare is the threat faced by coalition operations, originating from insurgent group activity [1], [2]. In many cases such groups are loosely and chaotically organised, but their ideals are sociologically and psychologically embedded across members such that the group has expected behaviours that can represent a major threat.…”

Section: Introductionmentioning

confidence: 99%

Parameterising the dynamics of inter-group conflict from real world data

Turner

Colombo

Whitaker

et al. 2017

2017 IEEE SmartWorld, Ubiquitous Intelligence &Amp; Computing, Advanced &Amp; Trusted Computed, Scalable Computing &Amp; Commun

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Abstract-Generative modelling of inter-group relations enables probabilistic forecasting of possible conflict for scenarios where real-world data is sparse. In order for such models to have relevance and integrity, it is important to ensure that realworld data is used to parameterise the model and verify its characteristics. In this paper we investigate how real-world datasets can be mapped into generative model parameters concerning group structures and behaviours. We highlight the issues involved and present a framework for classifying potential data based on three attributes: (i) inter-group structure, (ii) inter-group actions and (iii) impact of actions. We argue that these attributes are fundamental for benchmarking and developing generative models in the context of limited existing data on inter-group interaction.

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Intra-group Tension Under Inter-group Conflict: A Generative Model Using Group Social Norms and Identity

Cited by 4 publications

References 9 publications

The role of motifs in understanding behavior in social and engineered networks

The role of motifs in understanding behavior in social and engineered networks

Mathematical models for social group behavior

Parameterising the dynamics of inter-group conflict from real world data

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