scholarly journals Friendships and Social Networks in an Individual-Based Model of Primate Social Behaviour

2017 ◽  
Vol 20 (3) ◽  
Author(s):  
Ivan Puga-Gonzalez ◽  
Cedric Sueur
Keyword(s):  
Social Networks ◽  
Social Behaviour ◽  
Individual Based Model

scholarly journals Addressing Misinformation in Online Social Networks: Diverse Platforms and the Potential of Multiagent Trust Modeling

Information ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 539
Author(s):  
Robin Cohen ◽  
Karyn Moffatt ◽  
Amira Ghenai ◽  
Andy Yang ◽  
Margaret Corwin ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Social Networks ◽  
Social Networking ◽  
Older Adult ◽  
Online Social Networks ◽  
Social Behaviour ◽  
Data Science ◽  
Science Studies ◽  
Trust Modeling ◽  
The Future

In this paper, we explore how various social networking platforms currently support the spread of misinformation. We then examine the potential of a few specific multiagent trust modeling algorithms from artificial intelligence, towards detecting that misinformation. Our investigation reveals that specific requirements of each environment may require distinct solutions for the processing. This then leads to a higher-level proposal for the actions to be taken in order to judge trustworthiness. Our final reflection concerns what information should be provided to users, once there are suspected misleading posts. Our aim is to enlighten both the organizations that host social networking and the users of those platforms, and to promote steps forward for more pro-social behaviour in these environments. As a look to the future and the growing need to address this vital topic, we reflect as well on two related topics of possible interest: the case of older adult users and the potential to track misinformation through dedicated data science studies, of particular use for healthcare.

A full-scale agent-based model of Lombardy COVID-19 dynamics to explore social networks connectivity and vaccine impact on epidemic (Preprint)

2020 ◽  
Author(s):  
Giuseppe Giacopelli
Keyword(s):  
Social Networks ◽  
Full Scale ◽  
Agent Based Model ◽  
Individual Based Model ◽  
Agent Based ◽  
Vaccine Impact ◽  
The Impact

UNSTRUCTURED COVID-19 outbreak is an awful event. However it gives to the scientists the possibility to test theories about epidemic. The aim of this contribution is to propose a individual-based model of Lombardy COVID-19 outbreak at full-scale, where full-scale means that will be simulated all the 10 millions inhabitant population of Lombardy person by person, in a commercial computer. All this to test the impact of our daily actions in epidemic, investigate social networks connectivity and in the end have an insight on the impact of an hypothetical vaccine.

Mapping autism and schizophrenia onto the ontogenesis of social behaviour: A hierarchical-developmental rather than diametrical perspective

2008 ◽  
Vol 31 (3) ◽  
pp. 262-263 ◽  
Author(s):  
Ralf-Peter Behrendt
Keyword(s):  
Social Networks ◽  
Developmental Stage ◽  
Social Behaviour ◽  
Co Morbidity ◽  
Schizophrenic Patients ◽  
Interpersonal Concerns

AbstractCo-morbidity of schizophrenia and autism is low because interpersonal concerns of schizophrenic patients presuppose developmental achievements that are absent in autism. Autism may arise if primary anxiety is not overcome at a key developmental stage by affective synchronisation between infant and caregiver. Schizophrenic patients will have learned to regulate primitive anxiety by affectively attuning to narrow social networks but remain highly vulnerable to exclusion from larger groups.

scholarly journals Product Recommendation based on Sybil and Trusted Votes in Social Networks

2019 ◽  
Vol 8 (3) ◽  
pp. 5434-5440
Keyword(s):  
Social Networks ◽  
Community Detection ◽  
Online Social Networks ◽  
Social Behaviour ◽  
Social World ◽  
Detection Algorithm ◽  
Information Gathering ◽  
Online Environment ◽  
The Social ◽  
Community Detection Algorithm

Networks is a platform which is easily accessible by normal users worldwide. Online Social Networks facilitates users online to get registered with ease of speed and create their own accounts to communicate with the social world for information gathering. This platform allows everyone to get registered online irrespective of their social behaviour. Users here are creating duplicate accounts that is creating Sybil in the network. By this Sybil online Social Networks are suffering for different kinds of Sybil attacks online. In social networks user’s feedback and preferences play an important role in suggesting friends online or recommending products online. When collecting the feedback or preferences of any product online both Sybil user’s and real user’s data is considered as we are not differentiating the Sybil user or real user. From this products, recommended online will not have an efficient rating which would divert the buyers online. To over this problem we propose Sybil Community Detection Algorithm (SCD) and TrustRank Algorithm that bifurcates real user votes and Sybil users votes to fetch the efficient products online thus build secure online environment.

scholarly journals A full-scale agent-based model of Lombardy COVID-19 dynamics to explore social networks connectivity and vaccine impact on epidemic

2020 ◽  
Author(s):  
Giuseppe Giacopelli
Keyword(s):  
Social Networks ◽  
Full Scale ◽  
Agent Based Model ◽  
Individual Based Model ◽  
Agent Based ◽  
Vaccine Impact ◽  
The Impact

COVID-19 outbreak is an awful event. However it gives to the scientists the possibility to test theories about epidemic. The aim of this contribution is to propose a individual-based model of Lombardy COVID-19 outbreak at full-scale, where full-scale means that will be simulated all the 10 millions inhabitant population of Lombardy person by person, in a commercial computer. All this to test the impact of our daily actions in epidemic, investigate social networks connectivity and in the end have an insight on the impact of an hypothetical vaccine.

Skill-based engagement with a rich landscape of affordances as an alternative to thinking through other minds

2020 ◽  
Vol 43 ◽  
Author(s):  
Julian Kiverstein ◽  
Erik Rietveld
Keyword(s):  
Social Behaviour ◽  
Cultural Learning ◽  
Other Minds ◽  
Middle Way ◽  
Internalist Account

Abstract Veissière and colleagues make a valiant attempt at reconciling an internalist account of implicit cultural learning with an externalist account that understands social behaviour in terms of its environment-involving dynamics. However, unfortunately the author's attempt to forge a middle way between internalism and externalism fails. We argue their failure stems from the overly individualistic understanding of the perception of cultural affordances they propose.

Multilayer Social Networks

2016 ◽  
Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi
Keyword(s):  
Social Networks ◽  
Multilayer Social Networks

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

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