Mixed Method Social Network Analysis

This article outlines a mixed method approach to social network analysis combining techniques of organizational history development, inductive data structuring, and content analysis to offer a novel approach for network data construction and analysis. This approach provides researchers with a number of benefits over traditional sociometric or other interpersonal methodologies including the ability to investigate networks of greater scope, broader access to diverse social actors, reduced informant bias, and increased capability for longitudinal designs. After detailing this approach, we apply the method on a sample of 143 new ventures and suggest opportunities for general application in entrepreneurship, strategic management, and organizational behavior research.

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Aspects of Various Community Detection Algorithms in Social Network Analysis

Advanced Methodologies and Technologies in Media and Communications - Advances in Multimedia and Interactive Technologies ◽

10.4018/978-1-5225-7601-3.ch026 ◽

2019 ◽

pp. 327-341

Author(s):

Nicole Belinda Dillen ◽

Aruna Chakraborty

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Community Detection ◽

Overlapping Community Detection ◽

Detection Algorithms ◽

Novel Approach ◽

Recent Developments ◽

Overlapping Community ◽

Related Individuals

One of the most important aspects of social network analysis is community detection, which is used to categorize related individuals in a social network into groups or communities. The approach is quite similar to graph partitioning, and in fact, most detection algorithms rely on concepts from graph theory and sociology. The aim of this chapter is to aid a novice in the field of community detection by providing a wider perspective on some of the different detection algorithms available, including the more recent developments in this field. Five popular algorithms have been studied and explained, and a recent novel approach that was proposed by the authors has also been included. The chapter concludes by highlighting areas suitable for further research, specifically targeting overlapping community detection algorithms.

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Advancing clinical leadership to improve the implementation of evidence-based practice in surgery: a longitudinal mixed-method study protocol

Implementation Science ◽

10.1186/s13012-020-01063-2 ◽

2020 ◽

Vol 15 (1) ◽

Author(s):

Amy Grove ◽

Aileen Clarke ◽

Graeme Currie ◽

Andy Metcalfe ◽

Catherine Pope ◽

...

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Mixed Method ◽

Qualitative Data ◽

Mixed Method Study ◽

Evidence Based ◽

Theory Approach ◽

Cross Sectional ◽

Clinical Leadership

Abstract Background Clinical leadership is fundamental in facilitating service improvements in healthcare. Few studies have attempted to understand or model the different approaches to leadership which are used when promoting the uptake and implementation of evidence-based interventions. This research aims to uncover and explain how distributed clinical leadership can be developed and improved to enhance the use of evidence in practice. In doing so, this study examines implementation leadership in orthopaedic surgery to explain leadership as a collective endeavour which cannot be separated from the organisational context. Methods A mixed-method study consisting of longitudinal and cross-sectional interviews and an embedded social network analysis will be performed in six NHS hospitals. A social network analysis will be undertaken in each hospital to uncover the organisational networks, the focal leadership actors and information flows in each organisation. This will be followed by a series of repeated semi-structured interviews, conducted over 4 years, with orthopaedic surgeons and their professional networks. These longitudinal interviews will be supplemented by cross-sectional interviews with the national established surgical leaders. All qualitative data will be analysed using a constructivist grounded theory approach and integrated with the quantitative data. The participant narratives will enrich the social network to uncover the leadership configurations which exist, and how different configurations of leadership are functioning in practice to influence implementation processes and outcomes. Discussion The study findings will facilitate understanding about how and why different configurations of leadership develop and under what organisational conditions and circumstances they are able to flourish. The study will guide the development of leadership interventions that are grounded in the data and aimed at advancing leadership for service improvement in orthopaedics. The strength of the study lies in the combination of multi-component, multi-site, multi-agent methods to examine leadership processes in surgery. The findings may be limited by the practical challenges of longitudinal qualitative data collection, such as ensuring participant retention, which need to be balanced against the theoretical and empirical insights generated through this comprehensive exploration of leadership across and within a range of healthcare organisations.

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Explaining the Development of Information Security Climate and an Information Security Support Network: A Longitudinal Social Network Analysis

Australasian Journal of Information Systems ◽

10.3127/ajis.v23i0.1822 ◽

2019 ◽

Vol 23 ◽

Cited By ~ 1

Author(s):

Duy Dang-Pham ◽

Karlheinz Kautz ◽

Siddhi Pittayachawan ◽

Vince Bruno

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Information Security ◽

Support Network ◽

Novel Approach ◽

Individual Cognition ◽

Climate Perceptions ◽

Personal Advice ◽

Practical Recommendations

Behavioural information security (InfoSec) research has studied InfoSec at workplaces through the employees’ perceptions of InfoSec climate, which is determined by observable InfoSec practices performed by their colleagues and direct supervisors. Prior studies have identified the antecedents of a positive InfoSec climate, in particular socialisation through the employees’ discussions of InfoSec-related matters to explain the formation of InfoSec climate based on the employees’ individual cognition. We conceptualise six forms of socialisation as six networks, which comprise employees’ provisions of (1) work advice, (2) organisational updates, (3) personal advice, (4) trust for expertise, (5) InfoSec advice, and (6) InfoSec troubleshooting support. The adoption of a longitudinal social network analysis (SNA), called stochastic actor-oriented modelling (SAOM), enabled us to analyse the changes in the socialising patterns and the InfoSec climate perceptions over time. Consequently, this analysis explains the forming mechanisms of the employees’ InfoSec climate perceptions as well as their socialising process in greater detail. Our findings in relation to the forming mechanisms of InfoSec-related socialisation and InfoSec climate, provide practical recommendations to improve organisational InfoSec. This includes identifying influential employees to diffuse InfoSec knowledge within a workplace. Additionally, this research proposes a novel approach for InfoSec behavioural research through the adoption of SNA methods to study InfoSec-related phenomena.

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New Developments in Social Network Analysis

Annual Review of Organizational Psychology and Organizational Behavior ◽

10.1146/annurev-orgpsych-012420-090628 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Daniel J. Brass

Keyword(s):

Social Networks ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Organizational Behavior ◽

Annual Review ◽

Publication Date ◽

Research Directions ◽

New Research ◽

Conceptual Foundations

This review of social network analysis focuses on identifying recent trends in interpersonal social networks research in organizations, and generating new research directions, with an emphasis on conceptual foundations. It is organized around two broad social network topics: structural holes and brokerage and the nature of ties. New research directions include adding affect, behavior, and cognition to the traditional structural analysis of social networks, adopting an alter-centric perspective including a relational approach to ego and alters, moving beyond the triad in structural hole and brokerage research to consider alters as brokers, expanding the nature of ties to include negative, multiplex/dissonant, and dormant ties, and exploring the value of redundant ties. The challenge is to answer the question “What's next in social network analysis?” Expected final online publication date for the Annual Review of Organizational Psychology and Organizational Behavior, Volume 9 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Studying Discourse as Social Interaction: The Potential of Social Network Analysis for Discourse Studies

Educational Researcher ◽

10.3102/0013189x18777741 ◽

2018 ◽

Vol 47 (6) ◽

pp. 375-383 ◽

Cited By ~ 2

Author(s):

Christopher J. Wagner ◽

María González-Howard

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Classroom Discourse ◽

Learning Opportunities ◽

Social Phenomenon ◽

Novel Approach ◽

Discourse Studies ◽

Classroom Structures

Education researchers have extensively studied classroom discourse as a way to understand classroom structures and learning. This article proposes the use of social network analysis (SNA) as a method for discourse studies in education. SNA enables us to learn about the connections between persons and the patterns of relations within groups. This presents a novel approach to the study of discourse that may more accurately reflect current understandings of discourse as a social phenomenon. This article explains the theoretical links between SNA and the concept of discourse in education and then considers how SNA can be used to examine classroom discourse. A brief overview of promising methods is presented to provide examples of how SNA can be applied to discourse data. This article argues that continued exploration and applications of SNA could yield more complex understandings of the role of discourse in learning opportunities and outcomes.

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USING PAGERANK AND SOCIAL NETWORK ANALYSIS TO SPECIFY MENTAL HEALTH FACTORS

Proceedings of the Design Society ◽

10.1017/pds.2021.599 ◽

2021 ◽

Vol 1 ◽

pp. 3379-3388

Author(s):

Arsineh Boodaghian Asl ◽

Jayanth Raghothama ◽

Adam Darwich ◽

Sebastiaan Meijer

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Well Being ◽

Influential Factors ◽

System Perspective ◽

Novel Approach ◽

Wide Range ◽

Mental Health Factors ◽

Mental Well Being

AbstractVarious factors influence mental well-being, and span individual, social and familial levels. These factors are connected in many ways, forming a complex web of factors and providing pathways for developing programs to improve well-being and for further research. These factors can be studied individually using traditional methods and mapped together to be analyzed holistically from a complex system perspective. This study provides a novel approach using PageRank and social network analysis to understand such maps. The motives are: (1) to realize the most influential factors in such complex networks, (2) to understand factors that influence variations from different network aspects. A previously developed map for children's mental well-being was adopted to evaluate the approach. To achieve our motives, we have developed an approach using PageRank and Social Network Analysis. The results indicate that regardless of the network scale, two key factors called "Quantity and Quality of Relationships" and "Advocacy" can influence children's mental well-being significantly. Moreover, the divergence analysis reveals that one factor, "Recognition/Value Placed on well-being at School" causes a wide range of diffusion throughout the system.

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Data collection for mixed method approaches in social network analysis

Mixed Methods Social Network Analysis ◽

10.4324/9780429056826-4 ◽

2019 ◽

pp. 25-37 ◽

Cited By ~ 1

Author(s):

Manuel Längler ◽

Jasperina Brouwer ◽

Hans Gruber

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Data Collection ◽

Mixed Method

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An Exploratory Analysis Using Co-Authorship Network

Advances in Business Information Systems and Analytics - Machine Learning Techniques for Improved Business Analytics ◽

10.4018/978-1-5225-3534-8.ch008 ◽

2019 ◽

pp. 166-200

Author(s):

Burçin Güçlü ◽

Miguel Ángel Canela ◽

Inés Alegre

Keyword(s):

Social Networks ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Organizational Behavior ◽

Human Behavior ◽

Online Social Networks ◽

World Wide ◽

Academic Research ◽

E Mail

Social network analysis has been widely used by organizational behavior researchers to stress the importance of the context, social connections, and social structure on human behavior. In the last decade, social network analysis has emerged as one of the most useful techniques for exploring online social networks, world wide web, e-mail traffic, and logistic operations. In this chapter, the authors present an application of social network analysis techniques for academic research. The authors choose Kahneman and Tversky's prospect theory as the focus of their analysis and, based on that, develop a co-authorship structure that depicts in a clear manner the key authors and/or the researchers that dominate and bridge different sub-fields in the field of management. The authors discuss the implications of this study for academic research and management discipline.

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