A new model for evaluating the influence of social networks, social learning, and supportive policies on the desire of women for fertility

2020 ◽  
pp. 1-14
Author(s):  
Pei-Lin Chen ◽  
Tahereh Nazari Saman
Keyword(s):  
Social Networks ◽  
Social Learning ◽  
New Model

scholarly journals GAME: General Aggression Model in Education

2015 ◽  
Vol 2 (3) ◽  
Author(s):  
Dr. Tanu Tandon
Keyword(s):  
Grounded Theory ◽  
Social Learning ◽  
Social Cognitive ◽  
Developmental Model ◽  
Learning Theories ◽  
General Aggression Model ◽  
New Model ◽  
Grounded Theory Methodology ◽  
Women In India

Women in India have been victim of violence and discrimination since ages but this aggression has also led to empowerment of women in some cases. This study deals with study of such aggressive women who transformed their aggression to empowerment. Grounded theory methodology has been used to explore and understand the process and role of education in transformation. This study focuses on route aggression takes and role of education in channelizing the aggressive energy so as to lead to empowerment. General Aggression Model (GAM) given by Anderson and Bushman (2002) is a dynamic, social, cognitive developmental model which draws heavily on social-cognitive and social learning theories. Aggression depends on how an individual perceives and interprets his/her environment and people there in, this model has been revised and a new model has been devised namely General Aggression Model in Education or GAME, which shows path towards empowerment from aggression.

Social Learning Analytics

2021 ◽  
pp. 190-206
Author(s):  
Mustafa Şahin Bülbül
Keyword(s):  
Social Networks ◽  
Social Learning ◽  
Learning Analytics ◽  
Social Learning Analytics ◽  
Shed Light

Despite the idea that learning is individual, the YouTube channel has been examined to explain how learning is controlled in social networks. What kind of mechanism does the YouTube channel, which deeply influences the education world, work with and what does this structure tell the educators? What do data such as the number of views and comments on YouTube mean? Also, what kind of a model can be established between the video proposition system and our individual and social learning? This study has been prepared to shed light on the questions mentioned.

scholarly journals Quantum Probabilistic Models Using Feynman Diagram Rules for Better Understanding the Information Diffusion Dynamics in Online Social Networks

2020 ◽  
Vol 34 (10) ◽  
pp. 13730-13731
Author(s):  
Ece C. Mutlu
Keyword(s):  
Social Networks ◽  
Social Learning ◽  
Complex Systems ◽  
Bayesian Networks ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Probabilistic Models ◽  
Human Interaction ◽  
Multi Agent Systems ◽  
Diffusion Dynamics

This doctoral consortium presents an overview of my anticipated PhD dissertation which focuses on employing quantum Bayesian networks for social learning. The project, mainly, aims to expand the use of current quantum probabilistic models in human decision-making from two agents to multi-agent systems. First, I cultivate the classical Bayesian networks which are used to understand information diffusion through human interaction on online social networks (OSNs) by taking into account the relevance of multitude of social, psychological, behavioral and cognitive factors influencing the process of information transmission. Since quantum like models require quantum probability amplitudes, the complexity will be exponentially increased with increasing uncertainty in the complex system. Therefore, the research will be followed by a study on optimization of heuristics. Here, I suggest to use an belief entropy based heuristic approach. This research is an interdisciplinary research which is related with the branches of complex systems, quantum physics, network science, information theory, cognitive science and mathematics. Therefore, findings can contribute significantly to the areas related mainly with social learning behavior of people, and also to the aforementioned branches of complex systems. In addition, understanding the interactions in complex systems might be more viable via the findings of this research since probabilistic approaches are not only used for predictive purposes but also for explanatory aims.

Learning in Social Networks

2016 ◽  
pp. 503-542 ◽  
Author(s):  
Benjamin Golub ◽  
Evan Sadler
Keyword(s):  
Social Networks ◽  
Social Learning ◽  
Learning Theories ◽  
Social Connections ◽  
Network Centrality ◽  
Learning Models ◽  
Network Learning ◽  
Aggregation Of Information

This survey covers models of how agents update behaviors and beliefs using information conveyed through social connections. The chapter begins with sequential social learning models, in which each agent makes a decision once and for all after observing a subset of prior decisions; the discussion is organized around the concepts of diffusion and aggregation of information. Next, the chapter presents the DeGroot framework of average-based repeated updating, whose long- and medium-run dynamics can be completely characterized in terms of measures of network centrality and segregation. Finally, the chapter turns to various models of repeated updating that feature richer optimizing behavior, and concludes by urging the development of network learning theories that can deal adequately with the observed phenomenon of persistent disagreement.

scholarly journals Power Indices in the Context of Social Learning Behaviour in Social Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Ruili Shi ◽  
Chunxiang Guo ◽  
Xin Gu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Learning ◽  
Social Impact ◽  
Power Index ◽  
Decision Makers ◽  
Power Indices ◽  
Learning Efficiency ◽  
Relationship Closeness ◽  
The Social

This paper puts forward the concept of integrated power, synthetically measures the voters’ ability to influence the results of decision-making by influencing others through social learning, considering the interactions between decision-makers in social networks, and offers a method for measuring integrated power. Based on the theory and model of social learning, we analyze the influence of social learning on the voting process and power indices from the perspective of individuals’ professional level, position within the social network structure, relationship closeness, and learning efficiency. A measurement model of integrated power is constructed, and the variation in integrated power compared with that of the Banzhaf index is analyzed by numerical simulation. The results show that when the individual’s professional level is higher and closeness with neighboring decision-makers is greater, then the integrated power index is higher. An individual’s integrated power index may decrease when he/she changes from an isolated node to a nonisolated node, and then his/her integrated power will increase with the increases of neighbor nodes. Social learning efficiency can promote the integrated power of individuals with lower social impact and relationship closeness, but it is not beneficial for the core and influential members of the social network.

scholarly journals Influential Node Control Strategy for Opinion Evolution on Social Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Cheng Ju ◽  
Jinde Cao ◽  
Weiqi Zhang ◽  
Mengxin Ji
Keyword(s):  
Social Networks ◽  
Control Strategy ◽  
Small World ◽  
Opinion Dynamics ◽  
Node Degree ◽  
New Model ◽  
New Strategy ◽  
Influential Nodes ◽  
Basic Features ◽  
Opinion Evolution

We study opinion dynamics in social networks and present a new strategy to control the invasive opinion. A developed continuous-opinion evolution model is proposed to describe the mechanism of making decision in closed community. Two basic strategies of evolution are determined, and some basic features of our new model are analyzed. We study the different invasive strategies. It is shown via using Monte Carlo simulations that our new model shows different invulnerability with traditional model. Node degree and cohesion in invasive small-world community plays less significant role when the evolution of opinion is continuous rather than dichotomous. Using simulation, we find one kind of Influential Nodes that can affect the outcome dramatically, while these Influential Nodes are sensitive to their node degree and the evolution weight. Thus, we develop invasive control strategy based on these features.

Sign in / Sign up

Export Citation Format

Share Document