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

2019 ◽  
Vol 23 ◽  
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.

Aspects of Various Community Detection Algorithms in Social Network Analysis

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.

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

2018 ◽  
Vol 47 (6) ◽  
pp. 375-383 ◽  
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.

scholarly journals USING PAGERANK AND SOCIAL NETWORK ANALYSIS TO SPECIFY MENTAL HEALTH FACTORS

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.

Mixed Method Social Network Analysis

2016 ◽  
Vol 20 (2) ◽  
pp. 268-298 ◽  
Author(s):  
Trenton A. Williams ◽  
Dean A. Shepherd
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Organizational Behavior ◽  
Mixed Method ◽  
New Ventures ◽  
Organizational History ◽  
General Application ◽  
Social Actors ◽  
Novel Approach

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.

scholarly journals Challenges and Opportunities for Interprofessional Collaboration within the Post-disaster Psychosocial Support Network in a Terrorism Scenario in the Netherlands: A Network Analysis

2019 ◽  
Vol 34 (s1) ◽  
pp. s69-s69
Author(s):  
Jurriaan Jacobs ◽  
Jacklien Maessen ◽  
Michel Dückers
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
The Netherlands ◽  
Focus Groups ◽  
Psychosocial Support ◽  
Guideline Implementation ◽  
Support Network ◽  
Network Data ◽  
Post Disaster

Introduction:Post-disaster psychosocial support (PSS) is an indispensable element of disaster management. A variety of studies contributed to the development of guidelines, information about guideline implementation, and evidence-based practice, as well as the status of local PSS planning and delivery systems in different European regions. However, the multi-disciplinary nature of the organization of post-disaster PSS requires interprofessional and inter-organizational collaboration, but is presently insufficient institutionalized on individual, organizational, and governmental levels, locally, within the region, and nationally.Aim:Objective of this research is to map the existing post-disaster PSS network in the Netherlands in the context of a terrorism scenario, and to identify probable collaboration problems rooted in weak ties and lack of alignment between actors at different levels.Methods:Focus groups were organized in Belgium, France, Norway, and the United Kingdom to learn from the inter-agency response to recent terrorist attacks. Next, social network analysis methods were used to analyze the structure of the collaborative network for post-disaster PSS in the Netherlands. A scenario-based questionnaire was distributed amongst relevant stakeholders through snowballing methods. Respondents were asked to identify organizations they collaborate with on different PSS activities during the preparedness, acute, and recovery phase.Results:The international focus groups resulted in valuable lessons for the Dutch PSS network. Data collection for social network analysis is currently in progress. Based on previous research we expect limited ties between disciplines during the preparedness phase and during the “registration of affected persons” in the acute phase. Most of the interactions between agencies will be linked to one-stop-shop service delivery, and less to commemorations and health monitoring.Discussion:Lessons from the focus groups, verification of whether or not the expectations are supported by the social network data, and reflections on opportunities for improvement will be presented at the conference in Brisbane.

Aspects of Various Community Detection Algorithms in Social Network Analysis

2018 ◽  
pp. 6961-6972
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.

scholarly journals Mapping the knowledge flow in sustainable construction project teams using social network analysis

2017 ◽  
Vol 24 (2) ◽  
pp. 229-259 ◽  
Author(s):  
Veronika Lilly Meta Schröpfer ◽  
Joe Tah ◽  
Esra Kurul
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Construction Projects ◽  
Construction Project ◽  
Research Strategy ◽  
Knowledge Flows ◽  
Sustainable Construction ◽  
Content Type ◽  
Novel Approach

Purpose The purpose of this paper is to examine knowledge transfer (KT) practices in five construction projects delivering sustainable office buildings in Germany and the UK by using social network analysis (SNA). Design/methodology/approach Case studies were adopted as research strategy, with one construction project representing one case study. A combination of quantitative data, social network data and some qualitative data on perceptions of the sustainable construction process and its KT were collected through questionnaires. The data were analysed using a combination of descriptive statistics, cross-tabulations, content analysis and SNA. This resulted in a KT map of each sustainable construction project. Findings The findings resulted in a better understanding of how knowledge on sustainable construction is transferred and adopted. They show that large amounts of tacit knowledge were transferred through strong ties in sparse networks. Research limitations/implications The findings could offer a solution to secure a certain standard of sustainable building quality through improved KT. The findings indicate a need for further research and discussion on network density, tie strength and tacit KT. Originality/value This paper contributes to the literature on KT from a social network perspective. It provides a novel approach through combining concepts of network structure and relatedness in tie contents regarding specialised knowledge, i.e. sustainable construction knowledge. Thereby it provides a robust approach to mapping knowledge flows in office building projects that aim to achieve high levels of sustainability standards.

Uncovering the Cultural Beliefs in a Nascent Entrepreneurial Ecosystem

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Joshua E. Marineau ◽  
Onnolee Nordstrom
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Mental Models ◽  
Cultural Beliefs ◽  
Individual Characteristics ◽  
Cultural Consensus ◽  
Future Research ◽  
Entrepreneurial Ecosystem ◽  
Novel Approach

AbstractIn this paper, we use Cultural Consensus as a theory and methodology and collect and analyze individuals’ mental models of entrepreneurship. This novel approach, combined with social network analysis, allows us to empirically study the shared cultural beliefs present within a nascent EE. Based on this case, we determine that, in contrast to mature ecosystems, the cultural beliefs within this nascent entrepreneurial ecosystem clearly prioritize action and behavioral elements over individual characteristics or entrepreneurial-related outcomes. Thus, our study suggests that the cultural beliefs within early ecosystems are different than the cultural beliefs that underpin mature ecosystems. We discuss implications and future research related to these findings and this approach.

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