scholarly journals Visualizations of personal social networks on Facebook and community structure: an exploratory study

2017 ◽  
Author(s):  
Christina Gkini ◽  
Alexios Brailas
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Single Point ◽  
Community Formation ◽  
Structure Pattern ◽  
Diffusion Of Information ◽  
Qualitative Interpretation ◽  
Network Topologies ◽  
Personal Social Networks ◽  
And Diffusion

We studied the community structure pattern in the visualizations of ten personal social networks on Facebook at a single point in time. It seems to be a strong tendency towards community formation in online personal, social networks: somebody’s friends are usually also friends between them, forming subgroups of more densely connected nodes. Research on community structure in social networks usually focuses on the networks’ statistical properties. There is a need for qualitative studies bridging the gap between network topologies and their sociological implications. To this direction, visual representations of personal networks in social media could be a valuable source of empirical data for qualitative interpretation. Most of the personal social networks’ visualizations in the present study are very highly clustered with densely-knit overlapping subgroups of friends and interconnected between them through wide bridges. This network topology pattern seems to be quite efficient, allowing for a fast spread and diffusion of information across the whole social network.

scholarly journals Towards Increasing Feedbacks and Diffusion of Information in Social Networks

2016 ◽  
Vol 4 (1) ◽  
pp. 11
Author(s):  
Mohcine Kodad ◽  
El Miloud Jaara
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Survey ◽  
Collaborative Work ◽  
Diffusion Of Information ◽  
And Diffusion

The purpose of this document is to highlight two strategies which increased feedbacks and stimulated the diffusion of information in social networks. Starting by an online survey, which assists searchers in understanding the behavior of social network users, to define the problem. The information received with this survey has been tested on validation by an analyze on the most popular type of posting on social networks. The results of this study provided two strategies as a solution for the problem of dissatisfaction among users of social networks and to increase feedbacks and diffusion of information on social network. One strategy is manual and is based on the type of publication and the second strategy is automatically and takes the concept of collaborative work in to account

scholarly journals Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks

2021 ◽  
Vol 13 (3) ◽  
pp. 76
Author(s):  
Quintino Francesco Lotito ◽  
Davide Zanella ◽  
Paolo Casari
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Simulation Models ◽  
Epidemic Models ◽  
Time Varying ◽  
Fake News ◽  
Network Access ◽  
Spreading Process ◽  
Network Topologies ◽  
Access Patterns

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

scholarly journals Emergence and evolution of social networks through exploration of the Adjacent Possible space

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Enrico Ubaldi ◽  
Raffaella Burioni ◽  
Vittorio Loreto ◽  
Francesca Tria
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Social Interactions ◽  
Clustering Coefficient ◽  
Human Beings ◽  
Broad Distribution ◽  
Phone Calls ◽  
Dynamical Features ◽  
Twitter Users ◽  
American Physical

AbstractThe interactions among human beings represent the backbone of our societies. How people establish new connections and allocate their social interactions among them can reveal a lot of our social organisation. We leverage on a recent mathematical formalisation of the Adjacent Possible space to propose a microscopic model accounting for the growth and dynamics of social networks. At the individual’s level, our model correctly reproduces the rate at which people acquire new acquaintances as well as how they allocate their interactions among existing edges. On the macroscopic side, the model reproduces the key topological and dynamical features of social networks: the broad distribution of degree and activities, the average clustering coefficient and the community structure. The theory is born out in three diverse real-world social networks: the network of mentions between Twitter users, the network of co-authorship of the American Physical Society journals, and a mobile-phone-calls network.

Dynamic personal social networks

2003 ◽  
Vol 24 (3) ◽  
pp. 139-142 ◽  
Author(s):  
G. Henri ter Hofte ◽  
Ingrid Mulder
Keyword(s):  
Social Networks ◽  
Personal Social Networks
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