Bifurcation and control of a delayed diffusive logistic model in online social networks

2014 ◽  
Author(s):  
Linhe Zhu ◽  
Hongyong Zhao ◽  
Haiyan Wang
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Logistic Model ◽  
And Control

Display and control in online social spaces: Towards a typology of users

2016 ◽  
Vol 20 (3) ◽  
pp. 845-861 ◽  
Author(s):  
Alexandre Fortier ◽  
Jacquelyn Burkell
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Q Methodology ◽  
Personal Information ◽  
Public Spaces ◽  
Information Control ◽  
Different Types ◽  
Social Display ◽  
And Control

Earlier research using qualitative techniques suggests that the default conception of online social networks is as public spaces with little or no expectation of control over content or distribution of profile information. Some research, however, suggests that users within these spaces have different perspectives on information control and distribution. This study uses Q methodology to investigate subjective perspectives with respect to privacy of, and control over, Facebook profiles. The results suggests three different types of social media users: those who view profiles as spaces for controlled social display, exerting control over content or audience; those who treat their profiles as spaces for open social display, exercising little control over either content or audience; and those who view profiles as places to post personal information to a controlled audience. We argue that these different perspectives lead to different privacy needs and expectations.

A Parallel Neural Network Approach for Faster Rumor Identification in Online Social Networks

2019 ◽  
Vol 15 (4) ◽  
pp. 69-89 ◽  
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L D
Keyword(s):  
Neural Network ◽  
Social Networks ◽  
Online Social Networks ◽  
Activation Function ◽  
Network Approach ◽  
Neural Network Approach ◽  
Scale Free ◽  
Rumor Detection ◽  
Available Information ◽  
And Control

The unprecedented scale of rumor propagation in online social networks urges the necessity of faster rumor identification and control. The identification of rumors in the inception itself is imperative to bring down the harm it could cause to the society at large. But, the available information regarding rumors in inception stages is minimal. To identify rumors with data sparsity, we have proposed a twofold convolutional neural network approach with a new activation function which generalizes faster with higher accuracy. The proposed approach utilizes prominent features such as temporal and content for the classification. This rumor detection method is compared with the state-of-the-art rumor detection approaches and results prove the proposed method identifies rumor earlier than other approaches. Using this approach, the detected rumors with 88% accuracy and 92% precision for experimental datasets is 5% to 35% better than the existing approaches. This automated approach provides better results for larger and scale-free networks.

scholarly journals Goffman's Theory as a Framework for Analysis of Self Presentation on Online Social Networks

2019 ◽  
Vol 13 (2) ◽  
pp. 243-276 ◽  
Author(s):  
Lucie Merunková ◽  
Josef Šlerka
Keyword(s):  
Social Networks ◽  
Impression Management ◽  
Online Social Networks ◽  
Personal Information ◽  
Structured Interviews ◽  
Public Authorities ◽  
Self Presentation ◽  
Face To Face ◽  
The Social ◽  
And Control

To investigate how people form their identity on social networks and control the impressions they invoke in their audiences, we analyzed personal profiles of 50 university student Facebook users using Erving Gofmann´s dramaturgical theory. We identified five basic forms through which users create and present their identities: The Public diary, The Influencer, The Entertainer, Job and education and Hobby, as well as the appropriate secondary roles performed by users who interact with them.These findings are corroborated by 8 semi-structured interviews with respondents, which enable a more in-depth exploration of the way they use Facebook, the social interactions they participate in, their motivation for posting contributions, and how they engage in impression management, perceive privacy and resolve issues caused by multiple audiences.A better understanding of how privacy is conceived and what motivates users to share their personal information online is essential for public authorities’ cooperation on shaping company privacy policies and creation of appropriate legal regulations.The key results confirm the presence of conscious effort to make a desired impression and prove Goffman’s theory of face-to-face interactions to be relevant in the context of online social networks.

scholarly journals A User Centered Approach to Managing Privacy in Online Social Networks

10.28945/2247 ◽  
2015 ◽  
Author(s):  
Lila Ghemri
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Online Social Network ◽  
Web Based ◽  
Private Data ◽  
Privacy Violation ◽  
And Control ◽  
Different Levels ◽  
New Framework

Since their initial introduction in the early 90’s, the popularity of web based online social networking sites has been growing exponentially, encompassing millions of users. As these social networks continue to grow and become more popular, users’ different social circles (friends, family, and colleagues) are very likely to collide, as they all coexist under the same infrastructure. Considering the different levels of relationships between a user and their social circles, concerns about privacy arise. How does a user conceal private data? Who has access to it? And what is the most effective way in managing it? Many different approaches have been taken by online social network providers to give users more control over their data, but these methods have not always been affective, resulting in the misuse of the data or unintentional disclosure. We propose a new framework that aims at reducing risks of privacy violation by giving the user better and more intuitive ways to manage their social circles and control who accesses what type of data.

Sign in / Sign up

Export Citation Format

Share Document