DynComm

2021 ◽  
Vol 12 (4) ◽  
pp. 0-0
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Community Detection ◽  
Dynamic Networks ◽  
R Package ◽  
Research Area ◽  
Evolving Networks ◽  
The Social ◽  
Analysis Of Dynamics ◽  
Support Students

The analysis of dynamics in networks represents a great deal in the Social Network Analysis research area. To support students, teachers, developers, and researchers in this work, we introduce a novel R package, namely DynComm. It is designed to be a multi-language package used for community detection and analysis on dynamic networks. The package introduces interfaces to facilitate further developments and the addition of new and future developed algorithms to deal with community detection in evolving networks. This new package aims to abstract the programmatic interface of the algorithms, whether they are written in R or other languages, and expose them as functions in R.

Understanding Researchers Collaboration in eParticipation using Social Network Analysis

2015 ◽  
Vol 11 (4) ◽  
pp. 38-68
Author(s):  
Eleni Kaliva ◽  
Dimitrios Katsioulas ◽  
Efthimios Tambouris ◽  
Konstantinos Tarabanis
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Area ◽  
Core Network ◽  
Academic Field ◽  
The Social ◽  
High Degree ◽  
Political Priority ◽  
Scientific Collaborations

Over the past years electronic participation (eParticipation) became a political priority worldwide. Consequently, research on the field has dramatically grown. However, eParticipation is still an unconsolidated research area that lacks generally agreed upon definitions, research disciplines, methods and boundaries. The aim of this paper is to contribute to the establishment of the eParticipation identity by investigating the scientific collaborations in the domain. The study of the nature of academic collaboration reveals the structure and the intellectual roots of the research community and the most influential authors. The approach followed in this paper includes the construction of the co-authorship network and the calculation of the social network analysis (SNA) metrics that describe the nature of the collaboration. The results revealed that eParticipation is a rather active academic field in the last decade including a high degree of collaboration and a core network of very influential researchers.

scholarly journals Social Network Analysis, Ethics and LGPD, considerations in research

2021 ◽  
Vol 14 (2) ◽  
pp. 28-52
Author(s):  
Luiz Paulo Carvalho ◽  
Jonice Oliveira ◽  
Flávia Maria Santoro ◽  
Claudia Cappelli
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Construction ◽  
Personal Data ◽  
Research Area ◽  
Research Field ◽  
Data Driven ◽  
Brazilian Society ◽  
The Social

Data protection and data-driven solutions are two progressing areas permeating Brazilian society. This work presents an interdisciplinary theoretical approach related to Ethics, from the ethics in computing perspective; the LGPD, from the Law studies perspective; and the Social Network Analysis in Brazil, from the Informatics perspective. This research area utilizes personal data extensively for knowledge construction, with semantic contributions, analyzing the reality; or pragmatic, building artifacts. Challenges and inseparable issues are observed, exposed, and debated in this work. We present considerations combining the three topics, personal data in the research field of social networks in Brazil respecting the LGPD and ethics precepts.

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.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

scholarly journals Evaluation of Coordination of Emergency Response Team through the Social Network Analysis. Case Study: Oil and Gas Refinery

2015 ◽  
Vol 6 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Iraj Mohammadfam ◽  
Susan Bastani ◽  
Mahbobeh Esaghi ◽  
Rostam Golmohamadi ◽  
Ali Saee
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Emergency Response ◽  
Oil And Gas ◽  
The Social ◽  
Response Team ◽  
Gas Refinery

scholarly journals The use of social network methodological framework in nursing care to breastfeeding women

2009 ◽  
Vol 17 (3) ◽  
pp. 354-360 ◽  
Author(s):  
Maria Helena do Nascimento Souza ◽  
Ivis Emília de Oliveira Souza ◽  
Florence Romijn Tocantins
Keyword(s):  
Social Network ◽  
Social Context ◽  
Network Analysis ◽  
Nursing Care ◽  
Nursing Practice ◽  
Methodological Framework ◽  
Strong Bond ◽  
The People ◽  
Primary Network ◽  
The Social

This study aimed to discuss the contribution of the social network methodological framework in nursing care delivered to women who breastfeed their children up to six months of age. This qualitative study aimed to elaborate the social network map of 20 women through tape-recorded interview. Social network analysis evidenced a "strong" bond between these women and members from their primary network, especially friends, neighbors, mothers or with the child's father, who were reported as the people most involved in the breastfeeding period. The contribution of this framework to nursing practice is discussed, especially in care and research processes. We believe that nurses' appropriation of this framework can be an important support for efficacious actions, as well as to favor a broader perspective on the social context people experience.

The evolution of the intellectual structure of strategic management between 1980 and 2019

2020 ◽  
Vol 13 (4) ◽  
pp. 503-534
Author(s):  
Mehmet Ali Köseoğlu ◽  
John Parnell
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Strategic Management ◽  
Citation Analysis ◽  
Intellectual Structure ◽  
Future Directions ◽  
Content Type ◽  
The Social ◽  
Economic Foundation

PurposeThe authors evaluate the evolution of the intellectual structure of strategic management (SM) by employing a document co-citation analysis through a network analysis for academic citations in articles published in the Strategic Management Journal (SMJ).Design/methodology/approachThe authors employed the co-citation analysis through the social network analysis.FindingsThe authors outlined the evolution of the academic foundations of the structure and emphasized several domains. The economic foundation of SM research with macro and micro perspectives has generated a solid knowledge stock in the literature. Industrial organization (IO) psychology has also been another dominant foundation. Its robust development and extension in the literature have focused on cognitive issues in actors' behaviors as a behavioral foundation of SM. Methodological issues in SM research have become dominant between 2004 and 2011, but their influence has been inconsistent. The authors concluded by recommending future directions to increase maturity in the SM research domain.Originality/valueThis is the first paper to elucidate the intellectual structure of SM by adopting the co-citation analysis through the social network analysis.

scholarly journals Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis

2021 ◽  
Vol 5 (4) ◽  
pp. 697-704
Author(s):  
Aprillian Kartino ◽  
M. Khairul Anam ◽  
Rahmaddeni ◽  
Junadhi
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
Interaction Network ◽  
Analysis Method ◽  
The Social ◽  
The World ◽  
High Degree

Covid-19 is a disease of the virus that is shaking the world and has been designated by WHO as a pandemic. This case of Covid-19 can be a place of dissemination of disinformation that can be utilized by some parties. The dissemination of information in this day and age has turned to the internet, namely social media, Twitter is one of the social media that is often used by Indonesians and the data can be analyzed. This study uses the social network analysis method, conducted to be able to find nodes that affect the ongoing interaction in the interaction network of information dissemination related to Covid-19 in Indonesia and see if the node is directly proportional to the value of its popularity. As well as to know in identifying the source of Covid-19 information, whether dominated by competent Twitter accounts in their fields. The data examined 19,939 nodes and 12,304 edges were taken from data provided by the web academic.droneemprit.id on the project "Analisis Opini Persebaran Virus Corona di Media Sosial", using the period of December 2019 to December 2020 on social media Twitter. The results showed that the @do_ra_dong account is an influential actor with the highest degree centrality of 860 and the @detikcom account is the actor with the highest popularity value of follower rank of 0.994741605. Thus actors who have a high degree of centrality value do not necessarily have a high follower rank value anyway. The study ignores if there are buzzer accounts on Twitter.  

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