Exploring variation in active network size: Constraints and ego characteristics

“…Since women have been found to perform better on social problem tasks involving autobiographical memory, to access autobiographical information and emotions more often in their conversations, to have greater recall of their kin network and to include relatively more kin in their social networks than men, implying that they are better practised at accessing this information (Dunbar and Spoors 1995;Goddard et al 1998;Roberts et al 2008Roberts et al , 2009Salmon and Daly 1996;Sehulster 1995;Stiller and Dunbar 2007 ). This may suggest that, if the kin naming system is a schema, women should out-perform men because their regular use of the kinship schema will lead to higher levels of automation.…”

Section: Studymentioning

confidence: 99%

“…The authors concluded that this put the effect of social relationships on mortality risk on a par with quitting smoking and in excess of that associated with obesity or lack of exercise (Holt-Lunstad et al 2010). As a consequence, while maintaining ties within a network can be energetically and temporally costly (Roberts and Dunbar 2011a;Roberts et al 2009), and place a constraint on an individual's freedom to act due to the structural embeddedness of the network, inclusion within a social network can have a significant positive impact on survival.…”

Section: Introductionmentioning

confidence: 99%

Is Kinship a Schema? Moral Decisions and the Function of the Human Kin Naming System

Machin

Dunbar

2015

Adaptive Human Behavior and Physiology

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The human kinship system, and its associated terminology, bears the hallmarks of an evolutionary adaptation but its evolutionary origins have not been explored. We argue that the human kinship naming system is a schema that evolved to reduce the cognitive load of maintaining kinships, allowing the expansion of the human network and an increase in survival. We report on the results of two response time studies, using moral dilemmas as a proxy for relationship maintenance, which test the hypothesis. We find qualified support for our argument. Within the 50 layer of the social network kinships do impose less cognitive load than friendships allowing a saving in processing power and an increase in social network size beyond that seen in non-human primates. However, the result in the 150 layer is contrary to that posited by our hypothesis: kinships impose a greater load than friendships and this load is highest when refusing help to kin. We explore and discuss the influence on results within this outermost layer of the nature of response, the influence of the wider network and the temporal distance which exists between ego and alter at this level of the network.

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“…• Decay (due to no or neutral interactions) Empirical studies in the sociology field have figured out that most of social relationships decay over time if participants do not interact, although decay rate may vary depending on the strength of the relationships [19]. We follow this social fact so that Experience TI decays if there is no interaction after a period of time or interactions are neutral.…”

Section: B Experience Model In the Rek Trust Evaluationmentioning

confidence: 99%

From Personal Experience to Global Reputation for Trust Evaluation in the Social Internet of Things

Truong

Zhou

et al. 2017

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

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Abstract-Trust has been exploring in the era of Internet of Things (IoT) as an extension of the traditional triad of security, privacy and reliability for offering secure, reliable and seamless communications and services. It plays a crucial role in supporting IoT entities to reduce possible risks before making decisions. However, despite a large amount of trust-related research in IoT, a prevailing trust evaluation model has been still debatable and under development. In this article, we clarify the concept of trust in the Social Internet of Things (SIoT) ecosystems and propose a comprehensive trust model called REK that incorporates third-party opinions, experience and direct observation as the three Trust Indicators. As the convergence of the IoT and social network, the SIoT enables any types of entities (physical devices, smart agents and services) to establish their own social networks based on their owners relationships. We leverage this characteristic for inaugurating Experience and Reputation, which are originally two concepts from social networks, as the two paramount indicators for trust. The Experience and Reputation are characterized and modeled using mathematical analysis along with simulation experiments and analytical results. We believe our contributions offer better understandings of trust models and evaluation mechanisms in the SIoT environment, particularly the two Experience and Reputation models. This paper also opens important trust-related research directions in near future.

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Exploring variation in active network size: Constraints and ego characteristics

Cited by 365 publications

References 56 publications

Topography of social touching depends on emotional bonds between humans

Topography of social touching depends on emotional bonds between humans

Is Kinship a Schema? Moral Decisions and the Function of the Human Kin Naming System

From Personal Experience to Global Reputation for Trust Evaluation in the Social Internet of Things

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