scholarly journals Chronic health conditions and adolescent friendship: perspectives from social network analysis

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Emily Long ◽  
Tyson Barrett ◽  
Ginger Lockhart
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Chronic Health Conditions ◽  
Health Conditions ◽  
Exponential Random Graph Models ◽  
Chronic Health ◽  
Social Network Structure ◽  
Adolescent Friendship

Abstract Objective The current study uses methods from social network analysis to examine the relationship between chronic health conditions (CHCs) and adolescent friendships. Particular attention is given to the processes of peer marginalization, peer withdrawal and homophily related to CHCs. Methods Exponential random graph models were used to investigate the extent to which a CHC is associated with patterns in adolescent friendship connections, while controlling for important social network properties and covariates. The study uses cross-sectional data from six small US high schools (n = 461) within the National Longitudinal Study of Adolescent to Adult Health. Results Findings demonstrate no significant differences between adolescents with CHCs and adolescents without CHCs in the number of incoming friendship nominations (peer marginalization) or outgoing friendship nominations (peer withdrawal). In addition, similarity in CHCs (homophily) was not significantly related to friendship between two individuals. Conclusions In sum, the presence of an adolescent CHC was not significantly associated with adolescent social network structure, including peer marginalization, peer withdrawal, and homophily related to CHCs, after controlling for alternative social network processes. Although previous literature suggests that adolescents with CHCs experience negative social consequences, the current findings demonstrate that the social network structure of adolescents with CHCs did not differ significantly from that of their peers without CHCs. Thus, findings from the current study suggest that CHCs are not related to objective reductions in social connections.

scholarly journals Computational Propaganda in Hashtag Activism

2021 ◽  
Vol 13 (2) ◽  
pp. 251
Author(s):  
Andhika Kurniawan Pontoh
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Networks ◽  
Network Structure ◽  
Media Coverage ◽  
Public Attention ◽  
Political Actors ◽  
The Public ◽  
Social Network Structure

The hashtag (#) has an important role in gathering Internet users' support for opinion and value. Computational propaganda has an important role in hashtag activism. This study wants to examine the role of computational propaganda actors such as anonymous political accounts, fake accounts and bot in social media that is able to mobilize the public and also increase the impression of Twitter audiences. The trend of Twitter hashtag activism #BebaskanIBHRS and #NegaraDamaiTanpaFPI began with the arrest of the chairman of the Islamic Defenders Front (FPI) Habib Rizieq Shihab (HRS); the two trending hashtags massively influenced public opinion on Twitter on December 13-14 2020. This study uses a sample of 1000 tweets or conversations on each hashtags and uses Social Network Analysis (SNA) with the Netlytic tool which is able to provide quantitative values of communication networks, through the social network structure of #BebaskaniBHRS and #NegaraDamaiTanpaFPI. This study reveals how the network structure and what factors are carried out by anonymous political actors in carrying out computational propaganda. The results of this study reveal the hashtags activism #BebaskaniBHRS is much more capable of mobilizing the public and is able to generate greater impressions than #NegaraDamaiTanpaFPI. This is because #BebaskaniBHRS has a computational propaganda message in the form of a loaded language with a clear frame and the choice of words directly invites the Twitter public to get involved through a retweet another finding in this research shows computational propaganda movement in hashtag activism was carried out by large groups consisting of anonymous accounts and bot accounts on other side online media coverage about the trending of these hashtag's activism was also able to increasing public attention. Tagar (#) memiliki peran penting dalam mengumpulkan dukungan pengguna Internet terhadap suatu opini dan nilai. Komputasi propaganda memiliki peran penting dalam aktivisme tagar. Penelitian ini ingin mengkaji peran aktor komputasi propaganda seperti akun anonim politik, akun palsu dan bot di media sosial yang mampu memobilisasi publik dan juga meningkatkan kesan khalayak Twitter. Tren aktivisme tagar Twitter #BebaskanIBHRS dan #NegaraDamaiTanpaFPI dimulai dengan penangkapan ketua Front Pembela Islam (FPI) Habib Rizieq Shihab (HRS); kedua tagar yang sedang trending tersebut secara masif memengaruhi opini publik di Twitter pada 13-14 Desember 2020. Penelitian ini menggunakan sampel 1000 tweet atau percakapan pada masing-masing tagar serta menggunakan Social Network Analysis (SNA) dengan alat Netlytic yang mampu memberikan nilai kuantitatif jaringan komunikasi. Melalui struktur jejaring sosial #BebaskaniBHRS dan #NegaraDamaiTanpaFPI, kajian ini mengungkap seperti apa struktur jaringan komunikasi dan hal apa saja yang dilakukan oleh aktor politik anonim dalam melakukan komputasi propaganda. Hasil penelitian ini mengungkapkan bahwa aktivisme tagar #BebaskaniBHRS jauh lebih mampu memobilisasi publik dan mampu menghasilkan impresi yang lebih besar dibandingkan #NegaraDamaiTanpaFPI. Hal ini dikarenakan #BebaskaniBHRS memiliki pesan komputasi propaganda dalam bentuk bahasa yang sarat dengan bingkai yang jelas dan pilihan kata secara langsung mengajak publik Twitter untuk terlibat melalui retweet.Temuan lain dalam penelitian ini menunjukkan gerakan komputasi propaganda dalam aktivisme  tagar dilakukan oleh kelompok besar yang terdiri dari akun anonim dan akun bot di sisi lain liputan media daring tentang tren aktivisme tagar ini juga mampu meningkatkan atensi publik.

scholarly journals Investigation of Rater Effects Using Social Network Analysis and Exponential Random Graph Models

2017 ◽  
Vol 78 (3) ◽  
pp. 430-459 ◽  
Author(s):  
Iasonas Lamprianou
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Exponential Random Graph Models ◽  
Graph Models ◽  
High Stakes ◽  
Rating Data ◽  
New Approach ◽  
Exponential Random Graph ◽  
Rater Severity

It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as “markers” or “judges”) demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new methods to analyze rating data. We used simulated and empirical data from two high-stakes language assessments, to propose a new approach, based on social network analysis and exponential graph models, to evaluate the readiness of a group of raters for operational rating. The results of this innovative approach are compared with the results of a Rasch analysis, which is a well-established approach for the analysis of such data. We also demonstrate how the new approach can be practically used to investigate important research questions such as whether rater severity is stable across rating tasks. The merits of the new approach, and the consequences for practice are discussed.

scholarly journals Identifying Integration and Differentiation in a Hospital’s Logistical System: A social network analysis of a case study

2020 ◽  
Author(s):  
Annelies van der Ham ◽  
Frits Van Merode ◽  
Dirk Ruwaard ◽  
Arno Van Raak
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Organization Theory ◽  
Exploratory Study ◽  
Case Study Research ◽  
Study Research ◽  
And Performance

Abstract Background Integration, the coordination and alignment of tasks, has been promoted widely in order to improve the performance of hospitals. Both organization theory and social network analysis offer perspectives on integration. This exploratory study research aims to understand how a hospital’s logistical system works, and in particular to what extent there is integration and differentiation. More specifically, it first describes how a hospital organizes logistical processes; second, it identifies the agents and the interactions for organizing logistical processes, and, third, it establishes the extent to which tasks are segmented into subsystems, which is referred to as differentiation, and whether these tasks are coordinated and aligned, thus achieving integration.Methods The study is based on case study research carried out in a hospital in the Netherlands. All logistical tasks that are executed for surgery patients were studied. Using a mixed method, data were collected from the Hospital Information System (HIS), documentation, observations and interviews. These data were used to perform a social network analysis and calculate the network metrics of the hospital network.Results This paper shows that 23 tasks are executed by 635 different agents who interact through 31,499 interaction links. The social network of the hospital demonstrates both integration and differentiation. The network appears to function differently from what is assumed in literature, as the network does not reflect the formal organizational structure of the hospital, and tasks are mainly executed across functional silos. Nurses and physicians perform integrative tasks and two agents who mainly coordinate the tasks in the network, have no hierarchical position towards other agents. The HIS does not seem to fulfill the interactional needs of agents. Conclusions This exploratory study reveals the network structure of a hospital. The cross-functional collaboration, the integration found, and position of managers, coordinators, nurses and doctors suggests a possible gap between organizational perspectives on hospitals and reality. This research sets a basis for further research that should focus on the relation between network structure and performance, on how integration is achieved and in what way organization theory concepts and social network analysis could be used in conjunction with one another.

Social Network Analysis

2011 ◽  
pp. 1460-1469
Author(s):  
David J. Dekker ◽  
Paul H.J. Hendriks
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Development Project ◽  
Knowledge Networks ◽  
Knowledge Processes ◽  
Social Network Structure ◽  
Product Development Project ◽  
Practice Knowledge

In knowledge management (KM), one perspective is that knowledge resides in individuals who interact in groups. Concepts as communities-of-practice, knowledge networks, and “encultured knowledge” as the outcome of shared sense-making (Blackler, 1995) are built upon this perspective. Social network analysis focuses on the patterns of people’s interactions. This adds to KM theory a dimension that considers the effects of social structure on for example, knowledge creation, retention and dissemination. This article provides a short overview of consequences of social network structure on knowledge processes and explores how the insights generated by social network analysis are valuable to KM as diagnostic elements for drafting KM interventions. Relevance is apparent for management areas such as R&D alliances, product development, project management, and so forth.

Forms and Functions of Aggression in Adolescent Friendship Selection and Influence: A Longitudinal Social Network Analysis

2009 ◽  
Vol 19 (3) ◽  
pp. 515-534 ◽  
Author(s):  
Jelle J. Sijtsema ◽  
Tiina Ojanen ◽  
René Veenstra ◽  
Siegwart Lindenberg ◽  
Patricia H. Hawley ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Adolescent Friendship ◽  
Friendship Selection

INFORMATION EXCHANGES OF SOCIAL MEDIA EVANGELISTS DURING FLOOD: A SOCIAL NETWORK ANALYSIS

2016 ◽  
Vol 78 (9-3) ◽  
Author(s):  
Abdus-samad Temitope Olanrewaju ◽  
Rahayu Ahmad ◽  
Kamarul Faizal Hashim
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Information Dissemination ◽  
Network Structures ◽  
Analysis Technique ◽  
Types Of Information ◽  
Information Brokers

Information dissemination during disaster is very crucial, but inherits several complexities associated with the dynamic characteristics of the disaster. Social media evangelists (activists) play an important role in disseminating critical updates at on-site locations. However, there is limited understanding on the network structure formed and its evolution and the types of information shared. To address these questions, this study employs Social Network Analysis technique on a dataset containing 157 social media posts from an influential civilian fan page during Malaysia’s flood. The finding demonstrates three different network structures emerged during the flood period. The network structure evolves depending on the current state of the flood, the amount of information available and the need of information. Through content analysis, there were seven types of information exchanges discovered. These information exchanges evolved as the scale and magnitude of flood changes. In conclusion, this study shows the emergence of different network structures, density and identification of influential information brokers among civilians that use social media during disaster. Despite the low number of influential information brokers, they successfully manage their specific cluster in conveying information about the disaster and most importantly coordinating the rescue mission.

scholarly journals Using Qualitative Analysis to Assess a Model of Support for Online Health Communities for People Living with Chronic Health Conditions (Preprint)

2018 ◽  
Author(s):  
Brian M. Green ◽  
Kaitlyn Van Horn ◽  
Ketki Gupta ◽  
Amrita Bhowmick ◽  
Michael Booth
Keyword(s):  
Network Analysis ◽  
Qualitative Data ◽  
Pearson Correlation ◽  
Chronic Health Conditions ◽  
Health Conditions ◽  
Practical Significance ◽  
Chronic Health ◽  
Online Health Communities ◽  
Health Communities ◽  
Thematic Network Analysis

BACKGROUND Online health communities (OHC) can be a powerful tool to facilitate communication among patients, professionals and family members who live with or care for someone with a chronic health condition(s). Health Union LLC’s OHC model engages, empowers and encourages people to take an active role in their health by providing content that aligns with their needs and interests and by cultivating a safe environment where communication, understanding and meaningful relationships can thrive. OHCs included in this study target people living with multiple sclerosis, migraine, IBS, rheumatoid arthritis, lung cancer, and prostate cancer. OBJECTIVE Using qualitative methods we sought to determine if constructs in the Health Union OHC model are supported by themes identified in OHC participant comments. Key components of the model to be tested include: content tailored to needs of community, facilitation, and encouragement of social support, active moderation, opportunities for active and passive engagement, and transparency of community norms and rules. METHODS A sample of over 5800 comments exported from over 40 Facebook posts from 6 OHCs was analyzed using the Dedoose qualitative data analysis software. Comments from these Facebook posts were extracted, imported into Dedoose software and coded. Interrater reliability of initial coding was calculated using Pearson Correlation Coefficient. An exploratory approach was taken in the analysis and initial codes were grouped into thematic categories and then confirmed through thematic network/framework analysis using the Dedosse software tool. Thematic categories were compared for similarity and differences for each of the 6 OHCs, original post type, and by the extent of active moderation evident in each comment thread. RESULTS Qualitative thematic network analysis of posts and comments from 6 OHCs correspond to the primary components of the Health Union OHC model. This analysis suggests that the structural elements of the OHC model, including active site moderation, support high levels of community engagement and information sharing and mutual support of OHC participants. CONCLUSIONS Qualitative data from the 6 OHCs demonstrates the positive impact the community has on participants, often helping them reframe their health care experience and coping strategies. The principle of adaptive engagement is demonstrated by the thematic network analysis and illustrates the Health Union OHC model constructs. Different community segments have different patterns of engagement. Our primary focus on the content of participant comments in this analysis is a current limitation. While we also examine more passive methods of liking and sharing posts utilized by OHC participants, these may warrant further analysis. This study has practical significance as it helps to demonstrate the value of online health communities for people living with chronic health conditions by providing meaningful engagement, support, and information in an accessible environment.

scholarly journals Identifying Integration and Differentiation in a Hospital’s Logistical System: A social network analysis of a case study

2020 ◽  
Author(s):  
Annelies van der Ham ◽  
Frits Van Merode ◽  
Dirk Ruwaard ◽  
Arno Van Raak
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Organization Theory ◽  
Exploratory Study ◽  
Case Study Research ◽  
Study Research ◽  
And Performance

Abstract Background Integration, the coordination and alignment of tasks, has been promoted widely in order to improve the performance of hospitals. Both organization theory and social network analysis offer perspectives on integration. This exploratory study research aims to understand how a hospital’s logistical system works, and in particular to what extent there is integration and differentiation. More specifically, it first describes how a hospital organizes logistical processes; second, it identifies the agents and the interactions for organizing logistical processes, and, third, it establishes the extent to which tasks are segmented into subsystems, which is referred to as differentiation, and whether these tasks are coordinated and aligned, thus achieving integration. Methods The study is based on case study research carried out in a hospital in the Netherlands. All logistical tasks that are executed for surgery patients were studied. Using a mixed method, data were collected from the Hospital Information System (HIS), documentation, observations and interviews. These data were used to perform a social network analysis and calculate the network metrics of the hospital network. Results This paper shows that 23 tasks are executed by 635 different agents who interact through 31,499 interaction links. The social network of the hospital demonstrates both integration and differentiation. The network appears to function differently from what is assumed in literature, as the network does not reflect the formal organizational structure of the hospital, and tasks are mainly executed across functional silos. Nurses and physicians perform integrative tasks and two agents who mainly coordinate the tasks in the network, have no hierarchical position towards other agents. The HIS does not seem to fulfill the interactional needs of agents. Conclusions This exploratory study reveals the network structure of a hospital. The cross-functional collaboration, the integration found, and position of managers, coordinators, nurses and doctors suggests a possible gap between organizational perspectives on hospitals and reality. This research sets a basis for further research that should focus on the relation between network structure and performance, on how integration is achieved and in what way organization theory concepts and social network analysis could be used in conjunction with one another.

Sign in / Sign up

Export Citation Format

Share Document