scholarly journals An Agent-Based Social Network Model of Binge Drinking Among Dutch Adults

2013 ◽  
Vol 16 (2) ◽  
Author(s):  
Philippe Giabbanelli ◽  
Rik Crutzen
Keyword(s):  
Social Network ◽  
Binge Drinking ◽  
Network Model ◽  
Agent Based

scholarly journals Deep Learning Exploration of Agent-Based Social Network Model Parameters

2021 ◽  
Vol 4 ◽  
Author(s):  
Yohsuke Murase ◽  
Hang-Hyun Jo ◽  
János Török ◽  
János Kertész ◽  
Kimmo Kaski
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Model ◽  
Network Models ◽  
Agent Based Modeling ◽  
Training Data ◽  
Model Parameters ◽  
Social Phenomena ◽  
Agent Based ◽  
Input Parameters

Interactions between humans give rise to complex social networks that are characterized by heterogeneous degree distribution, weight-topology relation, overlapping community structure, and dynamics of links. Understanding these characteristics of social networks is the primary goal of their research as they constitute scaffolds for various emergent social phenomena from disease spreading to political movements. An appropriate tool for studying them is agent-based modeling, in which nodes, representing individuals, make decisions about creating and deleting links, thus yielding various macroscopic behavioral patterns. Here we focus on studying a generalization of the weighted social network model, being one of the most fundamental agent-based models for describing the formation of social ties and social networks. This generalized weighted social network (GWSN) model incorporates triadic closure, homophilic interactions, and various link termination mechanisms, which have been studied separately in the previous works. Accordingly, the GWSN model has an increased number of input parameters and the model behavior gets excessively complex, making it challenging to clarify the model behavior. We have executed massive simulations with a supercomputer and used the results as the training data for deep neural networks to conduct regression analysis for predicting the properties of the generated networks from the input parameters. The obtained regression model was also used for global sensitivity analysis to identify which parameters are influential or insignificant. We believe that this methodology is applicable for a large class of complex network models, thus opening the way for more realistic quantitative agent-based modeling.

Autonomy-oriented proximity mobile social network modeling in smart city for emergency rescue

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110612
Author(s):  
Zhao Chunxiao ◽  
Guo Junjie
Keyword(s):  
Social Network ◽  
Network Model ◽  
Smart City ◽  
Disaster Relief ◽  
Network Modeling ◽  
Mobile Social Network ◽  
Emergency Rescue ◽  
Routing Strategy ◽  
Social Network Modeling ◽  
Post Disaster

Nearest neighbor mobile social network means that movers approaching in position communicate through their social sensors, which is called Proximity Mobile Social Network. Proximity Mobile Social Network can provide more social and business opportunities for users. To carry out disaster relief work in post-disaster environment, we need to collect incident information during the search process and report to the sink in time. Proximity Mobile Social Network provides flexible systems for emergency handling and disaster relief. Therefore, how to find a better data forwarding and routing strategy is the key problem of post-disaster rescue, and the research of user mobility model is the basis of the above problems. This article presents an Autonomy-Oriented Proximity Mobile Social Network modeling for emergency rescue in smart city, which simulates the network operating environment. First, we verify the performance of Autonomy-Oriented Proximity Mobile Social Network model in terms of self-organization, scale-free, aggregation, and community structure. Then, the rescue efficiency is discussed through the coverage of mobile sensors. Finally, performance of the routing strategy based on Autonomy-Oriented Proximity Mobile Social Network model is analyzed, and the effectiveness of the method is proved.

Factors affecting BIM application in China: a social network model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shuangliang Tai ◽  
Yao Zhang ◽  
Ting Li
Keyword(s):  
Social Network ◽  
Network Model ◽  
Information Modeling ◽  
Information Communication ◽  
Key Factors ◽  
Content Type ◽  
Factors Affecting ◽  
Building Information ◽  
Management Modes ◽  
Definition Of

Purpose The purpose of this paper is to promote the application of building information modeling (BIM) in China’s construction industry, key factors and their relationships are explored. Design/methodology/approach Based on a literature review, 28 factors were extracted and their relationships (239 in total) obtained using the Delphi method. A social network model of the factors was constructed and factors were analyzed using social network analysis (SNA). Findings The top 10 key factors and their relationships were obtained using SNA. Among the top 10 critical factors, six were source factors. They were: training for the application of BIM, guidance from experts, proper management modes, efficient BIM teams, specifications and demonstrations and standards for building information communication. The other four factors included as follows: a willingness to accept BIM, knowledge of its value and benefits, the definition of its benefits and the availability of IT software and hardware. These were mediating factors that could further the influence of the source factors. Originality/value The results provide useful information for public agencies and professionals to understand the immediate and mediating influences of the factors on the application of BIM. Solutions and future efforts for different participants are presented to promote the application of BIM-based on the key factors and their relationships.

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