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.

Duality beyondPersons and Groups

2020 ◽  
pp. 391-413
Author(s):  
Sophie Mützel ◽  
Ronald Breiger
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Future Directions ◽  
Affiliation Networks ◽  
The Social ◽  
Recent Developments ◽  
Principle Of Duality ◽  
Seminal Article

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.

scholarly journals Scientific collaboration network ammong Brazilian universities

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Maria Isabel Escalona-Fernandez ◽  
Antonio Pulgarin-Guerrero ◽  
Ely Francina Tannuri de Oliveira ◽  
Maria Cláudia Cabrini Gracio
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scientific Collaboration ◽  
Methodological Approach ◽  
Scientific Production ◽  
Collaboration Network ◽  
Network Data ◽  
New Knowledge

This paper analyses the scientific collaboration network formed by the Brazilian universities that investigate in dentistry area. The constructed network is based on the published documents in the Scopus (Elsevier) database covering a period of 10 (ten) years. It is used social network analysis as the best methodological approach to visualize the capacity for collaboration, dissemination and transmission of new knowledge among universities. Cohesion and density of the collaboration network is analyzed, as well as the centrality of the universities as key-actors and the occurrence of subgroups within the network. Data were analyzed using the software UCINET and NetDraw. The number of documents published by each university was used as an indicator of its scientific production.

Social Network Analysis in Marketing

E-Marketing ◽  
2012 ◽  
pp. 185-197
Author(s):  
Przemyslaw Kazienko ◽  
Piotr Doskocz ◽  
Tomasz Kajdanowicz
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Network Data ◽  
Social Network Data ◽  
The Social ◽  
Targeted Marketing ◽  
Potential Customers ◽  
Demographic Features

The chapter describes a method how to perform a classification task without any demographic features and based only on the social network data. The concept of such collective classification facilitates to identify potential customers by means of services used or products purchased by the current customers, i.e. classes they belong to as well as using social relationships between the known and potential customers. As a result, a personalized offer can be prepared for the new clients. This innovative marketing method can boost targeted marketing campaigns.

Social Network Analysis in Marketing

2011 ◽  
pp. 271-283
Author(s):  
Przemyslaw Kazienko ◽  
Piotr Doskocz ◽  
Tomasz Kajdanowicz
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Network Data ◽  
Social Network Data ◽  
The Social ◽  
Targeted Marketing ◽  
Potential Customers ◽  
Demographic Features

The chapter describes a method how to perform a classification task without any demographic features and based only on the social network data. The concept of such collective classification facilitates to identify potential customers by means of services used or products purchased by the current customers, i.e. classes they belong to as well as using social relationships between the known and potential customers. As a result, a personalized offer can be prepared for the new clients. This innovative marketing method can boost targeted marketing campaigns.

Using Social Network Analysis (SNA) to Study Members and Activists of Political Parties

2020 ◽  
Vol 147-148 (1-2) ◽  
pp. 13-48
Author(s):  
Emilien Paulis
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Political Parties ◽  
Political Party ◽  
Methodological Approach ◽  
Network Data ◽  
Party Member ◽  
Party Membership ◽  
Local Party

This article explores the development of my PhD dissertation’s methodological approach, based on Social Network Analysis (SNA), or the collection and analysis of network data, in order to deal with political parties and their members (party membership). I extensively relied on this alternative, growing methodological background in three extents. First (1), SNA was used to analyze bibliographic references related to my dissertation topic, i.e. party membership studies, and identify the most central authors, thereby illustrating the literature review while describing their key contributions. Second (2), SNA was employed to collect and analyze network data likely to better grasp how interpersonal networks affect the probability for a random citizen to turn into party member, assuming that social influence matters in the process of joining a political party. Third (3), I further capitalized on SNA to deal with the question of party activism and why some members become active whereas others remain passive, arguing theoretically and showing empirically that part of the answer lies in members’ position within their local party branch’s social network. Each of these three applications is discussed in the light of the main methodological developments, the empirical findings and their interpretation, while shortcomings and research opportunities are more systematically highlighted at the end.

scholarly journals Common Permutation Methods in Animal Social Network Analysis Do Not Control for Non-independence

2021 ◽  
Author(s):  
Jordan D. A. Hart ◽  
Michael N. Weiss ◽  
Lauren J. N. Brent ◽  
Daniel W. Franks
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Regression Models ◽  
Permutation Tests ◽  
Network Data ◽  
P Values ◽  
Parametric Regression ◽  
Node Label ◽  
Parametric Regression Models

The non-independence of social network data is a cause for concern among behavioural ecologists conducting social network analysis. This has led to the adoption of several permutation-based methods for testing common hypotheses. One of the most common types of analysis is nodal regression, where the relationships between node-level network metrics and nodal covariates are analysed using a permutation technique known as node-label permutation. We show that, contrary to accepted wisdom, node-label permutations do not account for the types of non-independence assumed to exist in network data, because regression-based permutation tests still assume exchangeability of residuals. The same theoretical condition also applies to the quadratic assignment procedure (QAP), a permutation-based method often used for conducting dyadic regression. We highlight that node-label permutations produce the same p-values as equivalent parametric regression models, but that in the presence of confounds, parametric regression models produce more accurate effect size estimates. We also note that QAP only controls for a specific type of non-independence between edges that are connected to the same nodes, and that appropriate parametric regression models are also able to account for this type of non-independence. Based on this, we advocate the retirement of permutation tests for regression analyses, in favour of well-specified parametric models. Moving away from permutation-based methods will reduce over-reliance on p-values, generate more reliable estimates of effect sizes, and facilitate the adoption of more powerful types of statistical analysis.

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.

scholarly journals Epidemics and Networks: A Social Network Analysis of the Spread of COVID-19 in South Korea and Policy Implications

2020 ◽  
Author(s):  
Wonkwang Jo ◽  
Dukjin Chang ◽  
Myoungsoon You ◽  
Ghi-Hoon Ghim
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Metropolitan Areas ◽  
Structural Characteristics ◽  
Skewed Distribution ◽  
Policy Implications ◽  
Contact Tracing ◽  
Network Data ◽  
Network Change

Abstract This study estimates the COVID-19 infection network from actual data and draws on implications for policy and research. Using contact tracing information of 3,283 confirmed patients in Seoul metropolitan areas from Jan 20 to July 19, 2020, this study creates an infection network and analyzes its structural characteristics. The main results are as follows: (1) out-degrees follow an extremely positively skewed distribution, and (2) removing the top nodes on the out-degree significantly decreases the size of the infection network. (3) The indicators, which express the infectious power of the network, change according to governmental measures. Efforts to collect network data and analyze network structures are urgently required for the efficiency of governmental responses to COVID-19. Implications for better use of a metric such as R0 to estimate infection spread are also discussed.

Varieties of Networks and Their Characteristics

2020 ◽  
pp. 184-194
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Temporal Data ◽  
Twitter Activity ◽  
E Mail

Contemporary social network analysis deals with network data of varying nature. An important source of this variety comes from availability of continuous, temporal data from online and digitalized interactions between actors. E-mail exchanges or Twitter activity are some examples of such data. This chapter introduces terminology to classify network data according to its content. In addition, it exemplifies research on temporal data and methods used in analysis of such data.

Data Preprocessing for Dynamic Social Network Analysis

2013 ◽  
pp. 25-39 ◽  
Author(s):  
Preeti Gupta ◽  
Vishal Bhatnagar
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Data Preprocessing ◽  
Original Data ◽  
Network Data ◽  
Data Set ◽  
Social Network Data ◽  
Dynamic Social Network ◽  
The Social

The social network analysis is of significant interest in various application domains due to its inherent richness. Social network analysis like any other data analysis is limited by the quality and quantity of data and for which data preprocessing plays the key role. Before the discovery of useful information or pattern from the social network data set, the original data set must be converted to a suitable format. In this chapter we present various phases of social network data preprocessing. In this context, the authors discuss various challenges in each phase. The goal of this chapter is to illustrate the importance of data preprocessing for social network analysis.

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