scholarly journals Learning Dynamics in Social Networks

Econometrica ◽  
2021 ◽  
Vol 89 (6) ◽  
pp. 2601-2635 ◽  
Author(s):  
Simon Board ◽  
Moritz Meyer-ter-Vehn
Keyword(s):  
Social Networks ◽  
Differential Equations ◽  
Network Structure ◽  
Bayesian Learning ◽  
Empirical Work ◽  
Random Networks ◽  
Product Diffusion ◽  
Directed Networks ◽  
Learning Dynamics ◽  
The Impact

This paper proposes a tractable model of Bayesian learning on large random networks where agents choose whether to adopt an innovation. We study the impact of the network structure on learning dynamics and product diffusion. In directed networks, all direct and indirect links contribute to agents' learning. In comparison, learning and welfare are lower in undirected networks and networks with cliques. In a rich class of networks, behavior is described by a small number of differential equations, making the model useful for empirical work.

Modelling multi-topic information propagation in online social networks based on resource competition

2016 ◽  
Vol 43 (3) ◽  
pp. 342-355 ◽  
Author(s):  
Liyuan Sun ◽  
Yadong Zhou ◽  
Xiaohong Guan
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Online Social Networks ◽  
Resource Competition ◽  
Propagation Model ◽  
Small Scale ◽  
Model Parameters ◽  
Information Propagation ◽  
Practical Applications ◽  
The Impact

Understanding information propagation in online social networks is important in many practical applications and is of great interest to many researchers. The challenge with the existing propagation models lies in the requirement of complete network structure, topic-dependent model parameters and topic isolated spread assumption, etc. In this paper, we study the characteristics of multi-topic information propagation based on the data collected from Sina Weibo, one of the most popular microblogging services in China. We find that the daily total amount of user resources is finite and users’ attention transfers from one topic to another. This shows evidence on the competitions between multiple dynamical topics. According to these empirical observations, we develop a competition-based multi-topic information propagation model without social network structure. This model is built based on general mechanisms of resource competitions, i.e. attracting and distracting users’ attention, and considers the interactions of multiple topics. Simulation results show that the model can effectively produce topics with temporal popularity similar to the real data. The impact of model parameters is also analysed. It is found that topic arrival rate reflects the strength of competitions, and topic fitness is significant in modelling the small scale topic propagation.

scholarly journals How Clustering Affects Epidemics in Random Networks

2014 ◽  
Vol 46 (04) ◽  
pp. 985-1008 ◽  
Author(s):  
Emilie Coupechoux ◽  
Marc Lelarge
Keyword(s):  
Social Networks ◽  
Power Law ◽  
Degree Distribution ◽  
Growth Process ◽  
Threshold Model ◽  
Clustering Coefficient ◽  
Random Networks ◽  
New Ideas ◽  
The Impact ◽  
Analysis Of Social Networks

Motivated by the analysis of social networks, we study a model of random networks that has both a given degree distribution and a tunable clustering coefficient. We consider two types of growth process on these graphs that model the spread of new ideas, technologies, viruses, or worms: the diffusion model and the symmetric threshold model. For both models, we characterize conditions under which global cascades are possible and compute their size explicitly, as a function of the degree distribution and the clustering coefficient. Our results are applied to regular or power-law graphs with exponential cutoff and shed new light on the impact of clustering.

scholarly journals How Clustering Affects Epidemics in Random Networks

2014 ◽  
Vol 46 (4) ◽  
pp. 985-1008 ◽  
Author(s):  
Emilie Coupechoux ◽  
Marc Lelarge
Keyword(s):  
Social Networks ◽  
Power Law ◽  
Degree Distribution ◽  
Growth Process ◽  
Threshold Model ◽  
Clustering Coefficient ◽  
Random Networks ◽  
New Ideas ◽  
The Impact ◽  
Analysis Of Social Networks

Motivated by the analysis of social networks, we study a model of random networks that has both a given degree distribution and a tunable clustering coefficient. We consider two types of growth process on these graphs that model the spread of new ideas, technologies, viruses, or worms: the diffusion model and the symmetric threshold model. For both models, we characterize conditions under which global cascades are possible and compute their size explicitly, as a function of the degree distribution and the clustering coefficient. Our results are applied to regular or power-law graphs with exponential cutoff and shed new light on the impact of clustering.

scholarly journals Locational Contiguity and Business Continuity: Perceived Organizational Resilience of Small- and Medium-Sized Enterprises in U.K. Business Parks

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402092741
Author(s):  
Brahim Herbane
Keyword(s):  
Social Networks ◽  
Empirical Work ◽  
Business Continuity ◽  
Organizational Resilience ◽  
Senior Managers ◽  
The United Kingdom ◽  
And Performance ◽  
Using Data ◽  
The Impact ◽  
Formal Business

As the ability to respond and adapt to crises, we conceptualize and examine organizational resilience through four components (active, temporal, posture, and performance). This multidimensional view of resilience combines the perceptions of senior managers and other indicators including the presence and nature of formal business continuity management. This study examines whether relationships with neighboring firms in a business park substitute wider network relationships. Relationships between locational attributes (locational contiguity within a business park), entrepreneurs’ social networks, and the perceived resilience of small- and medium-sized enterprises (SMEs) in the United Kingdom are examined using data collected from 268 SMEs. Locational attributes are positively associated with organizational resilience (in both aggregated and constituent forms) while revealing an inverse relationship between social networks and perceived resilience. Importantly, the study contributes to a place-based view of resilience to explain why the impact of social networks differs from the positive associations that are found in prior theoretical and empirical work.

scholarly journals DISABLEMENT IN CONTEXT: DO SOCIAL NETWORKS MODERATE THE IMPACT OF INCREASING FUNCTIONAL IMPAIRMENT ON WELL-BEING?

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S565-S565
Author(s):  
William R McConnell ◽  
Robbie Dembo
Keyword(s):  
Older Adults ◽  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Social Participation ◽  
Functional Impairment ◽  
Social Activity ◽  
Functional Impairments ◽  
The Impact

Abstract Older adults with disabilities face a higher risk of experiencing poor health and social isolation in later life. Prior research has shown that social factors such as supportive relationships can modify disablement trajectories and reduce the likelihood of negative outcomes. Although research has considered the functional benefits of relationships through examining mechanisms like social support provision, the effects of network structure on the disablement process are not well understood. This study examines multiple social network mechanisms to explain the link between disability, health, and social participation among older adults. We ask, do social networks characteristics mediate or moderate the effects of increasing functional impairment on health and social participation? We analyze longitudinal panel data from the National Social Life, Health, and Aging Project 2005 & 2010, including 2,261 adults aged 57-85. Respondents named 9,587 network members in 2005. We model indicators of health and social participation at 5-year follow-up using trajectories of functional impairment and social network characteristics. We find that larger, denser, and more supportive networks are associated with better health and more frequent social activity at follow-up. Furthermore, social network structure mediates the relationship between increasing functional impairment and health, but moderates the effect of impairment on social participation. For example, participants with more dense networks are more likely to maintain high social activity at follow-up, even at relatively high levels of impairment. This study demonstrates that functional impairments are not inherently disabling. Instead, personal and social resources can reduce the potential burdens of impairment in individuals’ lives.

Loss distribution of systemic defaults in different interbank networks

2016 ◽  
Vol 27 (10) ◽  
pp. 1650121 ◽  
Author(s):  
Shouwei Li ◽  
Jianmin He
Keyword(s):  
Network Structure ◽  
Small World ◽  
Default Probability ◽  
Random Networks ◽  
Interbank Market ◽  
Small World Networks ◽  
Loss Distribution ◽  
Loss Given Default ◽  
Scale Free ◽  
The Impact

We analyze the impact of the network structure, the default probability and the loss given default (LGD) on the loss distribution of systemic defaults in the interbank market, where network structures analyzed include random networks, small-world networks and scale-free networks. We find that the network structure has little effect on the shape of the loss distribution, whereas the opposite is true to the default probability; the LGD changes the shape of the loss distribution significantly when default probabilities are high; the maximum of the possible loss is sensitive to the network structure and the LGD.

Influence of social networks on business processes’ development

2020 ◽  
Vol 19 (12) ◽  
pp. 2225-2252
Author(s):  
E.V. Popov ◽  
V.L. Simonova ◽  
O.V. Komarova ◽  
S.S. Kaigorodova
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Business Models ◽  
Business Processes ◽  
Digital Economy ◽  
Theoretical Understanding ◽  
Sales Channels ◽  
A Value ◽  
The Impact

Subject. The emergence of new ways of interaction between sellers and buyers, the formation of new sales channels and product promotion based on the use of digital economy tools is at the heart of improving the business processes. Social networks became a tool for development; their rapid growth necessitates theoretical understanding and identification of potential application in enterprise's business process digitalization. Objectives. We explore the role of social media in the digitalization of business processes, systematize the impact of social networks on business processes of enterprises in the digital economy. Methods. The theoretical and methodological analysis of social networks as a tool for digitalization of company's business processes rests on the content analysis of domestic and foreign scientific studies, comparison, generalization and systematization. Results. We highlight the key effects of the impact of social networks on the business processes of the company; show that the digitalization of business processes should be considered in the context of a value-based approach, aimed at creating a value through the algorithmization of company operations. We determine that social networks are one of the most important tools for digitalization of company's business processes, as they have a high organizational and management potential. We also systematize the effects of social media on company's business processes. Conclusions. We present theoretical provisions of the impact of social networks on business processes of enterprises, which will enable to model and organize ideas about the development of digital ecosystems and the formation of business models.

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