scholarly journals Generating a heterosexual bipartite network embedded in social network

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Asma Azizi ◽  
Zhuolin Qu ◽  
Bryan Lewis ◽  
James Mac Hyman
Keyword(s):  
Social Network ◽  
Real World ◽  
Large Scale ◽  
Social Contact ◽  
Contact Network ◽  
Bipartite Network ◽  
Sexual Networks ◽  
Sexual Network ◽  
Activity Data ◽  
The Social

AbstractWe describe an approach to generate a heterosexual network with a prescribed joint-degree distribution embedded in a prescribed large-scale social contact network. The structure of a sexual network plays an important role in how all sexually transmitted infections (STIs) spread. Generating an ensemble of networks that mimics the real-world is crucial to evaluating robust mitigation strategies for controlling STIs. Most of the current algorithms to generate sexual networks only use sexual activity data, such as the number of partners per month, to generate the sexual network. Real-world sexual networks also depend on biased mixing based on age, location, and social and work activities. We describe an approach to use a broad range of social activity data to generate possible heterosexual networks. We start with a large-scale simulation of thousands of people in a city as they go through their daily activities, including work, school, shopping, and activities at home. We extract a social network from these activities where the nodes are the people, and the edges indicate a social interaction, such as working in the same location. This social network captures the correlations between people of different ages, living in different locations, their economic status, and other demographic factors. We use the social contact network to define a bipartite heterosexual network that is embedded within an extended social network. The resulting sexual network captures the biased mixing inherent in the social network, and models based on this pairing of networks can be used to investigate novel intervention strategies based on the social contacts among infected people. We illustrate the approach in a model for the spread of chlamydia in the heterosexual network representing the young sexually active community in New Orleans.

Flawed Security of Social Network of Things

2018 ◽  
pp. 65-86
Author(s):  
Rohit Anand ◽  
Akash Sinha ◽  
Abhishek Bhardwaj ◽  
Aswin Sreeraj
Keyword(s):  
Social Network ◽  
Real World ◽  
Personal Data ◽  
Dynamic Structure ◽  
Security And Privacy ◽  
Human Intervention ◽  
Security Measures ◽  
The Social ◽  
Data Capturing ◽  
Shared Network

This chapter deals with the security flaws of social network of things. The network of things (NoT) is a dynamic structure that is basically an interface of real world and virtual world having capabilities of collection and sharing data over a shared network. The social network of things (SNoT) is a versatile way of connecting virtual and real world. Like any other device connected to internet, objects in SNoT are also vulnerable to the various security and privacy attacks. Generally, to secure Social Network of Things in which human intervention is absent, data capturing devices must be avoided. Types of security attacks that are huge threats to NoT as well as SNoT will be discussed in the chapter. The huge collection of information without necessary security measures allows an intruder to misuse the personal data of owner. Different types of attacks with reference to the different layers are also discussed in detail. The best possible potential solutions for the security of devices in SNoT will be considered.

Competence Management over Social Networks Through Dynamic Taxonomies

2013 ◽  
pp. 103-120
Author(s):  
Giuseppe Berio ◽  
Antonio Di Leva ◽  
Mounira Harzallah ◽  
Giovanni M. Sacco
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Real World ◽  
Reference Model ◽  
Effective Solution ◽  
Network Information ◽  
The Social ◽  
Competence Management

The exploitation and integration of social network information in a competence reference model (CRAI, Competence, Resource, Aspect, Individual) are discussed. The Social-CRAI model, which extends CRAI to social networks, provides an effective solution to this problem and is discussed in detail. Finally, dynamic taxonomies, a model supporting explorative conceptual search, are introduced and their use in the context of the Social-CRAI model for exploring retrieved information available in social networks is discussed. A real-world example is provided.

scholarly journals Construction of Regional Logistics Weighted Network Model and Its Robust optimization: Evidence from China

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Lizhao Yan ◽  
Yi Wen ◽  
Kok Lay Teo ◽  
Jian Liu ◽  
Fei Xu
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Large Scale ◽  
Analysis Method ◽  
Logistics Network ◽  
Regional Logistics ◽  
Logistics Networks ◽  
The Social ◽  
Weighted Model ◽  
New Perspective

In this paper, we construct a regional logistics model from a macroperspective. First, based on the gravity model, the index of logistics attraction between cities is established as the weight of the model, and hence the regional logistics weighted model is constructed. Next, we use the social network analysis method to analyze its structure and make specific recommendations for the construction of logistics networks. Finally, we analyze the model’s response to random attacks and deliberate attacks. From our study, it is found that when the failure nodes or edges reach a certain percentage, the regional logistics network will collapse on a large scale. Therefore, it is important to optimization the threshold of the regional logistics network. This clearly provides a new perspective for the study of the regional logistics networks.

scholarly journals Social networks strongly predict the gut microbiota of wild mice

2020 ◽  
Author(s):  
Aura Raulo ◽  
Bryony Allen ◽  
Tanya Troitsky ◽  
Arild Husby ◽  
Josh A Firth ◽  
...  
Keyword(s):  
Social Network ◽  
Gut Microbiota ◽  
Social Interactions ◽  
Tracking System ◽  
Group Living ◽  
Social Contact ◽  
Spatial Proximity ◽  
Activity Data ◽  
Wild Mice ◽  
Passive Tracking

AbstractThe mammalian gut teems with beneficial microbes, yet how hosts acquire these symbionts remains poorly understood. Research in primates suggests that microbes can be picked up via social contact, but the role of social interactions in non-group-living species remains unexplored. Here, we use a passive tracking system to collect high resolution spatiotemporal activity data from wild mice (Apodemus sylvaticus). Social network analysis revealed social association strength to be the strongest predictor of microbiota similarity among individuals, controlling for factors including spatial proximity and kinship, which had far smaller or nonsignificant effects. This social effect was limited to interactions involving males (male-male and male-female), implicating sex-dependent behaviours as driving processes. Social network position also predicted microbiota richness, with well-connected hub individuals having the most diverse microbiotas. Overall, these findings suggest social contact provides a key transmission pathway for gut symbionts even in relatively asocial mammals, that strongly shapes the adult gut microbiota. This work underlines the potential for individuals to pick up beneficial symbionts as well as pathogens from social interactions.

scholarly journals THE STUDY OF SELF-DETERMINED MOTIVATION OF STUDENTS IN THE CONTEXT OF DISTANCE LEARNING ACTIVITIES

2021 ◽  
Vol 31 (2) ◽  
pp. 226-238
Author(s):  
N.A. Khlybova ◽  
I.V. Tomicheva ◽  
I.V. Girenko
Keyword(s):  
Social Network ◽  
Distance Learning ◽  
Large Scale ◽  
Motivational Aspect ◽  
The Social ◽  
Online Distance Learning ◽  
Online Distance ◽  
The University ◽  
Effective Integration

The article examines the self-determined motivation of students studying at the V.I. Vernadsky Crimean Federal University (Simferopol) in the context of pedagogical activity using the social network VKONTAKTE as a platform for educational interaction and distance knowledge formation. The paper uses the theory of self-determination of Deci and Ryan, which provides an appropriate basis for assessing self-determined motivation in a targeted audience in the context of distance learning based on ICT. The results show that students are motivated to use the pages of the social network VKONTAKTE for educational purposes, which allows them to gain new knowledge and satisfaction from improving their own level of education. Taking into account the motivational aspect of the use of the social network in the university pedagogy of online distance learning, it can be concluded that it has a significant potential for large-scale and effective integration of ICT in higher education.

scholarly journals Social networks strongly predict the gut microbiota of wild mice

2021 ◽  
Author(s):  
Aura Raulo ◽  
Bryony E. Allen ◽  
Tanya Troitsky ◽  
Arild Husby ◽  
Josh A. Firth ◽  
...  
Keyword(s):  
Social Network ◽  
Gut Microbiota ◽  
Social Interactions ◽  
Tracking System ◽  
Group Living ◽  
Social Contact ◽  
Spatial Proximity ◽  
Activity Data ◽  
Wild Mice ◽  
Passive Tracking

AbstractThe mammalian gut teems with microbes, yet how hosts acquire these symbionts remains poorly understood. Research in primates suggests that microbes can be picked up via social contact, but the role of social interactions in non-group-living species remains underexplored. Here, we use a passive tracking system to collect high resolution spatiotemporal activity data from wild mice (Apodemus sylvaticus). Social network analysis revealed social association strength to be the strongest predictor of microbiota similarity among individuals, controlling for factors including spatial proximity and kinship, which had far smaller or nonsignificant effects. This social effect was limited to interactions involving males (male-male and male-female), implicating sex-dependent behaviours as driving processes. Social network position also predicted microbiota richness, with well-connected individuals having the most diverse microbiotas. Overall, these findings suggest social contact provides a key transmission pathway for gut symbionts even in relatively asocial mammals, that strongly shapes the adult gut microbiota. This work underlines the potential for individuals to pick up beneficial symbionts as well as pathogens from social interactions.

scholarly journals Spatial utilization predicts animal social contact networks are not scale-free

2017 ◽  
Vol 4 (12) ◽  
pp. 171209
Author(s):  
Alex James ◽  
Jeanette C. McLeod ◽  
Carlos Rouco ◽  
Kyle S. Richardson ◽  
Daniel M. Tompkins
Keyword(s):  
Network Architecture ◽  
Social Contact ◽  
Computational Effort ◽  
Contact Network ◽  
Brushtail Possum ◽  
Contact Networks ◽  
Scale Free ◽  
The Social ◽  
Social Contact Networks ◽  
Analytical Result

While heterogeneity in social behaviour has been described in many human contexts it is often assumed to be less common in the animal kingdom even though scale-free networks are observed. This homogeneity raises the question of whether the patterns of behaviour necessary to account for scale-free social contact networks, where the degree distribution follows a power law, i.e. a few individuals are very highly connected but most have only a few connections, occur in animals, or whether other mechanisms are needed to produce realistic contact network architectures. We develop a space-utilization model for individual animal behaviour to predict the individuals' social contact network. Using basic properties of the χ 2 distribution we present a simple analytical result that allows the model to give a range of predictions with minimal computational effort. The model results are tested on data collected in New Zealand for the social contact networks of the wild brushtail possum ( Trichosurus vulpecula ). Our model provides a better prediction of network architecture than other simple models, including a scale-free model.

scholarly journals Social networks influence farming practices and agrarian sustainability

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244619
Author(s):  
Amaia Albizua ◽  
Elena M. Bennett ◽  
Guillaume Larocque ◽  
Robert W. Krause ◽  
Unai Pascual
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Land Management ◽  
Agricultural Intensification ◽  
Large Scale ◽  
Management Practices ◽  
Farming Community ◽  
Social Ecological ◽  
The Social ◽  
The Impact

The social-ecological effects of agricultural intensification are complex. We explore farmers’ perceptions about the impacts of their land management and the impact of social information flows on their management through a case study in a farming community in Navarra, Spain, that is undergoing agricultural intensification due to adoption of large scale irrigation. We found that modern technology adopters are aware that their management practices often have negative social-ecological implications; by contrast, more traditional farmers tend to recognize their positive impacts on non-material benefits such as those linked with traditions and traditional knowledge, and climate regulation. We found that farmers’ awareness about nature contributions to people co-production and their land management decisions determine, in part, the structure of the social networks among the farming community. Since modern farmers are at the core of the social network, they are better able to control the information flow within the community. This has important implications, such as the fact that the traditional farmers, who are more aware of their impacts on the environment, rely on information controlled by more intensive modern farmers, potentially jeopardizing sustainable practices in this region. We suggest that this might be counteracted by helping traditional farmers obtain information tailored to their practices from outside the social network.

scholarly journals TensorCast: Forecasting Time-Evolving Networks with Contextual Information

2018 ◽  
Author(s):  
Miguel Araújo ◽  
Pedro Ribeiro ◽  
Christos Faloutsos
Keyword(s):  
Social Network ◽  
Real World ◽  
Large Scale ◽  
Information Sources ◽  
Contextual Information ◽  
Temporal Networks ◽  
Evolving Networks ◽  
Award Winning ◽  
Data Source

Can we forecast future connections in a social network? Can we predict who will start using a given hashtag in Twitter, leveraging contextual information such as who follows or retweets whom to improve our predictions? In this paper we present an abridged report of TensorCast, an award winning method for forecasting time-evolving networks, that uses coupled tensors to incorporate multiple information sources. TensorCast is scalable (linearithmic on the number of connections), effective (more precise than competing methods) and general (applicable to any data source representable by a tensor). We also showcase our method when applied to forecast two large scale heterogeneous real world temporal networks, namely Twitter and DBLP.

scholarly journals Graph, Spectra, Control and Epidemics: An Example with a SEIR Model

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2987
Author(s):  
Giacomo Aletti ◽  
Alessandro Benfenati ◽  
Giovanni Naldi
Keyword(s):  
Social Contact ◽  
Economic Cost ◽  
Population Based ◽  
Biological Data ◽  
Contact Network ◽  
Graph Spectra ◽  
Animal Populations ◽  
The Social ◽  
Spread Of Infection ◽  
Group Version

Networks and graphs offer a suitable and powerful framework for studying the spread of infection in human and animal populations. In the case of a heterogeneous population, the social contact network has a pivotal role in the analysis of directly transmitted infectious diseases. The literature presents several works where network-based models encompass realistic features (such as contacts networks or host–pathogen biological data), but analytical results are nonetheless scarce. As a significant example, in this paper, we develop a multi-group version of the epidemiological SEIR population-based model. Each group can represent a social subpopulation with the same habits or a group of geographically localized people. We consider also heterogeneity in the weighting of contacts between two groups. As a simple application, we propose a simple control algorithm in which we optimize the connection weights in order to minimize the combination between an economic cost and a social cost. Some numerical simulations are also provided.

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