Intra-group tension under inter-group conflict: a generative model using group social norms and identity

Group behavior is an important feature of conflict scenarios. Often such groups are chaotically organized, but their ideals are sociologically embedded across members such that the group has expected behavior that can represent a major threat. Therefore being able to model the evolution of groups on a generative basis, to anticipate their possible mutation, is valuable. However this is complex due to the diverse nature of human behavior and scenarios. In this paper we present an innovative approach to modeling these issues. Group identities are represented in terms of the behaviors (social norms) that members are expected to carry out towards other groups. Individuals predominantly compose their identity from the identity of the groups to which they belong, which is known to occur in situations of heightened conflict. The model introduced enables exploration of tensions associated with affiliation to multiple groups and the influence on inclusion and exclusion of individuals

A generative model for predicting terrorist incidents

A major concern in coalition peace-support operations is the incidence of terrorist activity. In this paper, we propose a generative model for the occurrence of the terrorist incidents, and illustrate that an increase in diversity, as measured by the number of different social groups to which that an individual belongs, is inversely correlated with the likelihood of a terrorist incident in the society. A generative model is one that can predict the likelihood of events in new contexts, as opposed to statistical models which are used to predict the future incidents based on the history of the incidents in an existing context. Generative models can be useful in planning for persistent Information Surveillance and Reconnaissance (ISR) since they allow an estimation of regions in the theater of operation where terrorist incidents may arise, and thus can be used to better allocate the assignment and deployment of ISR assets. In this paper, we present a taxonomy of terrorist incidents, identify factors related to occurrence of terrorist incidents, and provide a mathematical analysis calculating the likelihood of occurrence of terrorist incidents in three common real-life scenarios arising in peace-keeping operations

Intra-group tension under inter-group conflict: a generative model using group social norms and identity

Group behavior is an important feature of conflict scenarios. Often such groups are chaotically organized, but their ideals are sociologically embedded across members such that the group has expected behavior that can represent a major threat. Therefore being able to model the evolution of groups on a generative basis, to anticipate their possible mutation, is valuable. However this is complex due to the diverse nature of human behavior and scenarios. In this paper we present an innovative approach to modeling these issues. Group identities are represented in terms of the behaviors (social norms) that members are expected to carry out towards other groups. Individuals predominantly compose their identity from the identity of the groups to which they belong, which is known to occur in situations of heightened conflict. The model introduced enables exploration of tensions associated with affiliation to multiple groups and the influence on inclusion and exclusion of individuals

From evolution to revolution: understanding mutability in large and disruptive human groups

Over the last 70 years there has been a major shift in the threats to global peace. While the 1950's and 1960's were characterised by the cold war and the arms race, many security threats are now characterised by group behaviours that are disruptive, subversive or extreme. In many cases such groups are loosely and chaotically organised, but their ideals are sociologically and psychologically embedded in group members to the extent that the group represents a major threat. As a result, insights into how human groups form, emerge and change are critical, but surprisingly limited insights into the mutability of human groups exist. In this paper we argue that important clues to understand the mutability of groups come from examining the evolutionary origins of human behaviour. In particular, groups have been instrumental in human evolution, used as a basis to derive survival advantage, leaving all humans with a basic disposition to navigate the world through social networking and managing their presence in a group. From this analysis we present five critical features of social groups that govern mutability, relating to social norms, individual standing, status rivalry, ingroup bias and cooperation. We argue that understanding how these five dimensions interact and evolve can provide new insights into group mutation and evolution. Importantly, these features lend themselves to digital modeling. Therefore computational simulation can support generative exploration of groups and the discovery of latent factors, relevant to both internal group and external group modelling. Finally we consider the role of online social media in relation to understanding the mutability of groups. This can play an active role in supporting collective behaviour, and analysis of social media in the context of the five dimensions of group mutability provides a fresh basis to interpret the forces affecting groups

Evolution of cooperation in device-to-device communication

Device-to-device (D2D) communications are a promising paradigm to improve spectral efficiency in cellular wireless networks by enabling peer to peer communication. In particular, short D2D links can be used to relay data to reduce the burden on core infrastructure. However, this relies on some mechanism to either enforce or incentivise nodes to donate their resources in order to act as a relay without any guarantee that this will be reciprocated in the future. Indirect reciprocity has been well studied from the perspective of human behaviour, proposing mechanisms and conditions under which such behaviour naturally evolves. In this paper we consider D2D networks that formulate the decision to share resources as a donation game using a model of social comparison and examine the conditions under which cooperation evolves without the need for a central authority. Experimentation shows that the emergence of cooperation is sensitive to network conditions, such as node density and noise

Push or delay? Decomposing Smartphone notification response behaviour

Smartphone notifications are often delivered without considering user interruptibility, potentially causing frustration for the recipient. Therefore research in this area has concerned finding contexts where interruptions are better received. The typical convention for monitoring interruption behaviour assumes binary actions, where a response is either completed or not at all. However, in reality a user may partially respond to an interruption, such as reacting to an audible alert or exploring which application caused it. Consequently we present a multi-step model of interruptibility that allows assessment of both partial and complete notification responses. Through a 6-month in-the-wild case study of 11,346 to-do list reminders from 93 users, we find support for reducing false-negative classification of interruptibility. Additionally, we find that different response behaviour is correlated with different contexts and that these behaviours are predictable with similar accuracy to complete responses

Interruptibility prediction for ubiquitous systems: conventions and new directions from a growing field

When should a machine attempt to communicate with a user? This is a historical problem that has been studied since the rise of personal computing. More recently, the emergence of pervasive technologies such as the smartphone have extended the problem to be ever-present in our daily lives, opening up new opportunities for context awareness through data collection and reasoning. Complementary to this there has been increasing interest in techniques to intelligently synchronise interruptions with human behaviour and cognition. However, it is increasingly challenging to categorise new developments, which are often scenario specific or scope a problem with particular unique features. In this paper we present a meta-analysis of this area, decomposing and comparing historical and recent works that seek to understand and predict how users will perceive and respond to interruptions. In doing so we identify research gaps, questions and opportunities that characterise this important emerging field for pervasive technology

Decentralised detection of periodic encounter communities in opportunistic networks

We tackle the problem of individuals being able to self-detect the encounter communities within which they periodically occur. This has widespread applicability, not least for future communication systems where content can be locally shared via wireless opportunistic networking when devices carried by participants come into close range. In this paper, we introduce a comprehensive model and decentralised algorithm to accomplish the detection of periodic communities in opportunistic networks. To the best of our knowledge, this is the first decentralised algorithm for the detection of periodic communities. We investigate the behaviour of our approach both analytically and with real-world data

New frontiers for crowdsourcing: The extended mind

We introduce the concept of extended mind crowdsourcing (EMC) which capitalises on the way in which humans naturally extend their cognition into the environment, using external objects such as smartphones and applications to augment their mental capacity. This phenomenon means that human computation is embedded in data and devices, representing a new way through which human cognition can be accessed for collective discoveries. We relate EMC to existing sociological and psychological concepts and argue that it lies at the intersection of human computation, social computing and crowdsourcing. EMC is a way in which new problems and discoveries can be tackled, for example as necessitated by “wicked” problems, ethnography and culture. We relate EMC to diverse disciplines and point to ways in which the concept may develop in future. We exemplify EMC by presenting a case study where participation in location-based social networks is used to discover the correlation between mobility and human personality traits. This has involved participation from 43 countries and resulted in analysis of over half a million check-ins at street-level locations