Social brain network correlates with real-life social network in individuals with schizophrenia and social anhedonia

AbstractSelf-control is vital for a wide range of outcomes across our lifespan, yet the developmental trajectory of its core components during adolescence remains elusive. Many adolescents can successfully regulate their behavior even when they do not show strong activation in brain regions typically recruited during self-control in adults. Thus, adolescents may rely on other neural and cognitive resources to compensate, including daily experiences navigating and managing complex social relationships that likely bolster self-control processes. Here, we tested whether activity and connectivity in brain systems associated with social cognition (i.e., self-processing and mentalizing) facilitated successful self-control. We measured brain activity using fMRI as 62 adolescents completed a Go/No-Go response inhibition task. Recruitment of social brain systems, especially the self-processing system, was associated with better response inhibition in adolescents. Interestingly, the reliance on the self-processing system was stronger in adolescents with weaker activation in the canonical response inhibition system, suggesting a compensatory role for social brain systems during adolescent development. Furthermore, we examined the importance of social context by computing the size, number of communities, and modularity of our participants’ real-life social network. We found that adolescents with more friends and more communities in their social networks demonstrated a stronger relationship between response inhibition and recruitment of social brain systems. Collectively, our results identify the importance of social context and its moderating role on the relationship between brain activity and behavior. Furthermore, our results indicate a critical role for social brain systems during the developmental trajectory of self-control throughout adolescence.Significance StatementWe employed a network neuroscience approach to investigate the role of social context and social brain systems in facilitating self-control in adolescents. We found that recruitment of social brain systems was associated with better response inhibition in adolescents, especially for adolescents with weaker activation in the response inhibition system. Moreover, adolescents with more friends and communities in their social networks showed stronger relationships between response inhibition and recruitment of social brain systems. Our results advance understanding of how brain systems facilitate self-control in adolescents, and how these brain responses are associated with features of an adolescent’s real-life social network. Bringing together findings related to brain networks and social networks provides key insights into how biology and environment mutually influence development.

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The emergence of a theta social brain network during infancy

NeuroImage ◽

10.1016/j.neuroimage.2021.118298 ◽

2021 ◽

pp. 118298

Author(s):

Bauke van der Velde ◽

Tonya White ◽

Prof. Chantal Kemner

Keyword(s):

Brain Network ◽

Social Brain

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A Novel Spatio-Temporal Access Control Model for Online Social Networks and Visual Verification

International Journal of Cloud Applications and Computing ◽

10.4018/ijcac.2021040102 ◽

2021 ◽

Vol 11 (2) ◽

pp. 17-31

Author(s):

Lanfang Zhang ◽

Zhiyong Zhang ◽

Ting Zhao

Keyword(s):

Social Network ◽

Access Control ◽

Online Social Networks ◽

Online Social Network ◽

Rapid Development ◽

Real Life ◽

Control Model ◽

Mobile Internet ◽

Access Control Model ◽

Spatio Temporal

With the rapid development of mobile internet, a large number of online social networking platforms and tools have been widely applied. As a classic method for protecting the privacy and information security of social users, access control technology is evolving with the spatio-temporal change of social application requirements and scenarios. However, nowadays there is a lack of effective theoretical model of social spatio-temporal access control as a guide. This paper proposed a novel spatio-temporal access control model for online social network (STAC) and its visual verification, combined with the advantages of discretionary access control, using formal language to describe the access control rules based on spatio-temporal, and real-life scenarios for access control policy description, realizes a more fine-grained access control mechanism for social network. By using the access control verification tool ACPT developed by NIST to visually verify the proposed model, the security and effectiveness of the STAC model are proved.

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Features of behavior of Russian and American students on social network Facebook

Alma mater Vestnik Vysshey Shkoly ◽

10.20339/am.04-21.119 ◽

2021 ◽

pp. 119-123

Author(s):

M.I. Krishtal ◽

◽

A.V. Shchekoturov

Keyword(s):

Social Capital ◽

Social Network ◽

Student Behavior ◽

Social Activism ◽

Real Life ◽

The United States ◽

Public And Private ◽

The Social ◽

American Students ◽

Making Friends

Presented is the analysis of peculiarities of behavior of Russian and American students in the social network Facebook. The focus of the study is on what activities students of the two countries are most often engaged in, as well as on what motives they motivate when adding users to the personal list of friends. The main method of research is a formalized interview (N = 266). Students of two higher educational institutions located in Kaliningrad (Russia) and Philadelphia (USA) were interviewed. In anticipation of the analysis, according to the functionality, the types of activities on Facebook were highlighted, i.e. social, functional and cognitive. Also forms of activity were divided into public and private according to the nature of their manifestation (open or hidden). The motives for making friends were typologized according to the user’s orientation towards the development of “binding” or “connecting” social capital. As a result of the analysis, it was revealed that students from the United States are more likely to engage in public activities on Facebook than students from Russia, which is expressed in more active commenting on posts, publishing content on their personal page and friends’ pages. Russian students prefer private activities (chat and viewing other people’s pages). The functional type of activity, expressed in the use of gaming and non-gaming applications, turned out to be the most unpopular form of pastime on Facebook among students in both countries. It was also found that students at two universities are more focused on the development of “connecting” social capital. At the same time, for Russian students the dating factor in real life does not act as an important motive for adding friends to the list as for American ones. It is suggested that the basis for the differences discovered are the features of the cultural environments in which students live. The Russian environment involves more cautious participation in public life, the American stimulates social activism. Significant gender differences in peculiarities of student behavior in Facebook network could not be identified.

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Measuring the Impact of Social Media

Social Knowledge ◽

10.4018/978-1-60960-203-1.ch002 ◽

2011 ◽

pp. 24-36 ◽

Cited By ~ 8

Author(s):

Kimiz Dalkir

Keyword(s):

Social Media ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Evaluation Method ◽

Real Life ◽

Work Processes ◽

The Social ◽

Post Test ◽

The Impact

This chapter focuses on a method, social network analysis (SNA) that can be used to assess the quantity and quality of connection, communication and collaboration mediated by social tools in an organization. An organization, in the Canadian public sector, is used as a real-life case study to illustrate how SNA can be used in a pre-test/post-test evaluation design to conduct a comparative assessment of methods that can be used before, during and after the implementation of organizational change in work processes. The same evaluation method can be used to assess the impact of introducing new social media such as wikis, expertise locator systems, blogs, Twitter and so on. In other words, while traditional pre-test/post-test designs can be easily applied to social media, the social media tools themselves can be added to the assessment toolkit. Social network analysis in particular is a good candidate to analyze the connections between people and content as well as people with other people.

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Novel Node Centrality-Based Efficient Empirical Robustness Assessment for Directed Network

Complexity ◽

10.1155/2020/8715619 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Xiaolong Deng ◽

Hao Ding ◽

Yong Chen ◽

Cai Chen ◽

Tiejun Lv

Keyword(s):

Social Network ◽

Vulnerability Assessment ◽

Online Social Networks ◽

Information Transfer ◽

Large Scale ◽

Real Life ◽

Clustering Coefficient ◽

Network Robustness ◽

Directed Network ◽

Online Social Media

In recent years, while extensive researches on various networks properties have been proposed and accomplished, little has been proposed and done on network robustness and node vulnerability assessment under cascades in directed large-scale online community networks. In essential, an online directed social network is a group-centered and information spread-dominated online platform which is very different from the traditional undirected social network. Some further research studies have indicated that the online social network has high robustness to random removals of nodes but fails to the intentional attacks, particularly to those attacks based on node betweenness or node directed coefficient. To explore on the robustness of directed social network, in this article, we have proposed two novel node centralities of ITG (information transfer gain-based probability clustering coefficient) and I M p v (directed path-based node importance centrality). These two new centrality models are designed to capture this cascading effect in directed online social networks. Furthermore, we also propose a new and highly efficient computing method based on iterations for I M p v . Then, with the abundant experiments on the synthetic signed network and real-life networks derived from directed online social media and directed human mobile phone calling network, it has been proved that our ITG and I M p v based on directed social network robustness and node vulnerability assessment method is more accurate, efficient, and faster than several traditional centrality methods such as degree and betweenness. And we also have proposed the solid reasoning and proof process of iteration times k in computation of I M p v . To the best knowledge of us, our research has drawn some new light on the leading edge of robustness on the directed social network.

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Nexus Between Social Network, Social Media Use, and Loneliness

Innovative Management and Business Practices in Asia - Advances in Human Resources Management and Organizational Development ◽

10.4018/978-1-7998-1566-2.ch012 ◽

2020 ◽

pp. 228-243

Author(s):

Md. Aminul Islam ◽

Bezon Kumar

Keyword(s):

Social Media ◽

Social Network ◽

Correlation Matrix ◽

Positive Relationship ◽

Media Use ◽

Negative Relationship ◽

Real Life ◽

Primary Data ◽

Social Media Use ◽

Facebook Use

This paper mainly explores how real-life social network and social media use are related to loneliness among university students in Bangladesh. To carry out this paper, primary data and several methods are used. This paper uses Lubben Social Network Scale and UCLA loneliness scale to measure the level of real life social network and loneliness, respectively. Besides Pearson's partial correlation matrix is used to find out the correlation between social network, social media use, and loneliness. The study finds that students are averagely engaged in real-life social network and moderately lonely. The study also finds a significantly positive relationship between social media (Facebook) use and loneliness, and a significantly negative relationship between real life social network and loneliness. This paper calls for the students to be careful in using social media and be engaged more in real life social network to avoid loneliness.

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Understanding attribute and social circle correlation in social networks

TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES ◽

10.3906/elk-1806-91 ◽

2019 ◽

pp. 1228-1242

Author(s):

PRANAV NERURKAR ◽

MADHAV CHANDANE ◽

SUNIL BHIRUD

Keyword(s):

Social Networks ◽

Social Network ◽

Online Social Network ◽

Real Life ◽

Coarse Grained ◽

Unified Framework ◽

Community Discovery ◽

Social Circle ◽

The Social ◽

Circle Formation

Social circles, groups, lists, etc. are functionalities that allow users of online social network (OSN) platforms to manually organize their social media contacts. However, this facility provided by OSNs has not received appreciation from users due to the tedious nature of the task of organizing the ones that are only contacted periodically. In view of the numerous benefits of this functionality, it may be advantageous to investigate measures that lead to enhancements in its efficacy by allowing for automatic creation of customized groups of users (social circles, groups, lists, etc). The field of study for this purpose, i.e. creating coarse-grained descriptions from data, consists of two families of techniques, community discovery and clustering. These approaches are infeasible for the purpose of automation of social circle creation as they fail on social networks. A reason for this failure could be lack of knowledge of the global structure of the social network or the sparsity that exists in data from social networking websites. As individuals do in real life, OSN clients dependably attempt to broaden their groups of contacts in order to fulfill different social demands. This means that ‘homophily’ would exist among OSN users and prove useful in the task of social circle detection. Based on this intuition, the current inquiry is focused on understanding ‘homophily’ and its role in the process of social circle formation. Extensive experiments are performed on egocentric networks (ego is user, alters are friends) extracted from prominent OSNs like Facebook, Twitter, and Google+. The results of these experiments are used to propose a unified framework: feature extraction for social circles discovery (FESC). FESC detects social circles by jointly modeling ego-net topology and attributes of alters. The performance of FESC is compared with standard benchmark frameworks using metrics like edit distance, modularity, and running time to highlight its efficacy.

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