scholarly journals Interprofessional Relationships in the Field of Obesity: Data from Canada

2010 ◽  
Vol 1 (2) ◽  
Author(s):  
Jenny Godley ◽  
Shelly Russell-Mayhew
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Empirical Studies ◽  
Research Work ◽  
Clinical Work ◽  
Interprofessional Relations ◽  
Working Relationships ◽  
Interprofessional Practice ◽  
Conducting Research

Background: While it is generally acknowledged that an interprofessional approach is necessary to treat and prevent obesity, there have been few empirical studies examining the working relationships of professionals in the obesity field.Methods: In this article social network analysis is used to examine the working relationships of 111 attendees, representing eleven different health professions, at the first National Obesity Summit in Canada. We assessed the extent of engagement in interprofessional relations across four activities: discussion, gathering information, providing care, and conducting research. We also examined attitudes toward interprofessional practice.Findings: On average, respondents reported that approximately 75% of the people they work with are from other professions. Attitudes toward interprofessional practice were generally positive, and did not vary significantly across professions. Interestingly, attitudes were not related to actual interprofessional relations in our sample. In terms of work type, we found that respondents who were engaged in both clinical and research work had the largest networks and had the highest percentage of interprofessional contacts in their discussion and research networks.Conclusions: Overall, the results suggest that within our sample of professionals working in the field of obesity, interprofessional practice is held in high regard as a concept. The results also suggest that members of professions that combine both research and clinical work are most likely to engage in interprofessional relationships. This article illustrates the utility of social network analysis to assess the extent of interprofessional relationships among those working in a particular healthcare field.

Collaboration Networks of the Implementation Science Centers for Cancer Control (ISC3): A Social Network Analysis

2021 ◽  
Author(s):  
Rebekah R Jacob ◽  
Ariella R Korn ◽  
Grace C Huang ◽  
Douglas Easterling ◽  
Daniel A Gundersen ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Implementation Science ◽  
Scientific Collaboration ◽  
Cancer Control ◽  
First Year ◽  
Science Centers ◽  
Policy Dissemination ◽  
Conducting Research

Abstract Background: Multi-center research initiatives offer opportunities to develop and strengthen connections among researchers. These initiatives often have goals of increased scientific collaboration which can be examined using social network analysis.Methods: The National Cancer Institute (NCI)-funded Implementation Science Centers in Cancer Control (ISC3) initiative conducted an online social network survey in its first year of funding (2020) to examine early scientific linkages among members (faculty, staff, trainees) and recognize areas for network growth. Members of the seven funded centers and NCI program staff identified collaborations in: planning/conducting research, capacity building, product development, scientific dissemination, practice/policy dissemination.Results: Of the 192 invitees, 182 network members completed the survey (95%). The most prevalent roles were faculty (60%) and research staff (24%). Almost one-quarter (23%) of members reported advanced expertise in implementation science (IS), 42% intermediate, and 35% beginner. Most members were female (69%) and white (79%). Across all collaboration activities, the network had a density of 14%, suggesting high cohesion for its first year. One-third (33%) of collaboration ties were between members from different centers. Degree centralization (0.33) and betweenness centralization (0.07) measures suggest a fairly saturated network (no one or few central member(s) holding all connections). The most prevalent and densely connected collaboration network was for planning/conducting research (1470 ties; 8% density). Practice/policy dissemination had the fewest collaboration ties (284), lowest density (3%), and largest number of non-connected members (n=43). Median degree (number of collaborations) varied across member characteristics and collaboration activities. Members with advanced IS expertise were more connected than intermediate/beginner groups for most activities (e.g., advanced IS members had a median of 24 capacity building collaborations (range: 4-58) vs. intermediate (median 9; range 2-53) and beginner (median 7; range 1-49) members. The number of practice/policy dissemination collaborations were similarly low across IS expertise levels (median degree 3 for advanced, 2 intermediate, 2 beginner). Conclusions: Results provide important directions for interventions within the ISC3 network to increase scientific collaboration and capacity, with a focus on growing cross-center collaborations and increasing engagement of under-represented groups. Findings will be used to capture infrastructure development as part of the initiative’s evaluation.

scholarly journals Exploring intellectual capital through social network analysis: a conceptual framework

2011 ◽  
Vol 59 (2) ◽  
pp. 361-364
Author(s):  
Ivana Tichá
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Conceptual Framework ◽  
Intellectual Capital ◽  
Empirical Studies ◽  
Relational Capital ◽  
Future Earning ◽  
External Relationships ◽  
Relational Resources

The purpose of this paper is to develop a framework to assess intellectual capital. Intellectual capital is a key element in an organization’s future earning potential. Theoretical and empirical studies show that it is the unique combination of the different elements of intellectual capital and tangible investments that determines an enterprise´s competitive advantage. Intellectual capital has been defined as the combination of an organization´s human, organizational and relational resources and activities. It includes the knowledge, skills, experience and abilities of the employees, its R&D activities, organizational, routines, procedures, systems, databases and its Intellectual Property Rights, as well as all the resources linked to its external relationships, such as with its customers, suppliers, R&D partners, etc. This paper focuses on the relational capital and attempts to suggest a conceptual framework to assess this part of intellectual capital applying social network analysis approach. The SNA approach allows for mapping and measuring of relationships and flows between, people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The conceptual framework is developed for the assessment of collaborative networks in the Czech higher education sector as the representation of its relational capital. It also builds on the previous work aiming at proposal of methodology guiding efforts to report intellectual capital at the Czech public universities.

scholarly journals Detecting Influencers in Social Media Using Social Network Analysis (SNA)

2018 ◽  
Vol 7 (4.38) ◽  
pp. 950 ◽  
Author(s):  
Siti Nurulain Mohd Rum ◽  
Razali Yaakob ◽  
Lilly Suriani Affendey
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Work ◽  
Modern Society ◽  
Business World ◽  
Management And Development ◽  
Use Of Social Media ◽  
Commercial Organizations

Social media has now become a key part of life in modern society; it is a place where people share their ideas, view, emotions, and sentiments. The explosion in the popularity of social media has led to an immense increase in data over the past few years. Users engage with this platform to share their experiences, feelings, and opinions on a broad range of topics, such as politics, personalities, news, products or events. Social media has also become a phenomenal platform that provides a powerful way for businesses to enhance their prospects and reach customers. Extracting and interpreting information from user-generated content is a trending topic in the scientific community as well as in the business world, and has attracted the interest of many commercial organizations. With the wise use of social media, the marketing process for promoting products and brands can be accelerated to reach the target audience. The beauty and health industry is one of the industries that make use of this platform as their digital marketing solution to integrate communications. Recently, many leading companies and brands have used digital influencers as their strategy for marketing campaigns in management and development. Therefore, the analysis of information extracted from social media is of great importance offering valuable insights and where the importance of each actor or individual in social media can be identified.  This can be achieved through the use of Social Network Analysis (SNA).  This research work aims at probing the effectiveness of SNA in social media in detecting the influencers in the area of beauty and health.   

scholarly journals Social Network Analysis (SNA) applied to current issues. Guidelines for its implementation in research and management projects

AWARI ◽  
2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Laura Teves ◽  
Jorge Julián Cueto
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Professional Training ◽  
Research Work ◽  
Model Approximation ◽  
Public And Private ◽  
Relational Approach ◽  
Training Courses ◽  
Development And Management

Social Network Analysis (SNA) has become the most demanded relational approach in the field of basic science and applied science in the last 20 years. Researchers and professionals from traditional social, natural, and exact disciplines agree on the interest in what some identify as the paradigm across the field of traditional sciences problems. While SNA deepens and grows in its developments, analysis, and tools, the demand for courses of graduate and postgraduate academic training increases; as well as the instances of professional updating in both public and private development and management sectors. Based on the supposition that both sectors are related with research work trajectories rooted in institutional and current issues, in this work we aim to present the basic guidelines of our strategies for putting together courses about SNA. Considering three levels based on epistemological, methodological, and transference criteria for the resolution of problems, we propose five lines to be taken into consideration in order to know, develop and apply relational research. The procedures for the design of tools that will allow the collection and construction of databases or the identification of appropriate information for a study of SNA. The analytical path must be explained both in its complexity of combined methods and in the strategies for the identification of patterns as well as the construction of models. Finally, the problems and study frameworks, the research procedures, and the transference instances can be controlled and assessed by testing results and model approximation. Academic and professional training courses provide tools for the appreciation of SNA conceptual fields together with the approximation and delimitation of feasible empiric problems to be studied by SNA.

Nethnography and Social Network Analysis for Studying Online Social Space

2022 ◽  
pp. 227-247
Author(s):  
Gloria Ziglioli ◽  
Alhassan Yakubu Alhassan
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Space ◽  
Social Research ◽  
Empirical Studies ◽  
Methodological Framework ◽  
Ethical Challenges ◽  
Social Spaces ◽  
Methodological Debate

This chapter contributes to the current methodological debate on digital, internet-based studies in social research. Based upon an introductive analysis of the research's perspectives, trajectories, and stages that have brought the online social spaces into social research, the chapter focuses on the advantages of combining quanti-quali approaches for approaching online complexity. In particular, the authors offer a deep discussion concerning the value, the methodological, and ethical challenges of netnography and social network analysis (SNA) methods for inquiring online social research by proposing a possible emerging methodological framework guiding further empirical studies.

Ikenet: Social network analysis of e-mail traffic in the Eisenhower Leadership Development Program

2007 ◽  
Author(s):  
Ian McCulloh ◽  
Grace Garcia ◽  
Kelsey Tardieu ◽  
Jennifer MacGibbon ◽  
Heather Dye ◽  
...  
Keyword(s):  
Social Network ◽  
Leadership Development ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Development Program ◽  
Leadership Development Program ◽  
E Mail
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