Bibliometric Analysis of the Tertiary Study on Agile Software Development using Social Network Analysis

2020 ◽  
Author(s):  
Egemen Bayram ◽  
Buket Dogan ◽  
Volkan Tunali
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Software Development ◽  
Bibliometric Analysis ◽  
Agile Software Development ◽  
Agile Software ◽  
Tertiary Study

Introduction

2020 ◽  
pp. xxii-13
Author(s):  
Ryan Light ◽  
James Moody
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Bibliometric Analysis ◽  
Social Life ◽  
New Directions ◽  
Central Paradigm

This chapter provides an introduction to this volume on social networks. It argues that social network analysis is greater than a method or data, but serves as a central paradigm for understanding social life. The chapter offers evidence of the influence of social network analysis with a bibliometric analysis of research on social networks. This analysis underscores how pervasive network analysis has become and highlights key theoretical and methodological concerns. It also introduces the sections of the volume broadly structured around theory, methods, broad conceptualizations like culture and temporality, and disciplinary contributions. The chapter concludes by discussing several promising new directions in the field of social network analysis.

Systematic literature reviews in agile software development: A tertiary study

2017 ◽  
Vol 85 ◽  
pp. 60-70 ◽  
Author(s):  
Rashina Hoda ◽  
Norsaremah Salleh ◽  
John Grundy ◽  
Hui Mien Tee
Keyword(s):  
Software Development ◽  
Agile Software Development ◽  
Literature Reviews ◽  
Agile Software ◽  
Tertiary Study

scholarly journals Assessing the impact of socio-technical congruence in software development: a systematic literature review

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Binish Raza ◽  
◽  
Rodina Ahmad ◽  
Mohd H.N.M Nasir ◽  
Shukor S.M Fauzi ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Literature Review ◽  
Software Development ◽  
Systematic Literature Review ◽  
Measurement Techniques ◽  
Evolutionary Trends ◽  
Team Members ◽  
The Impact

Software development is a critical task that depends on coordination among team members and organizational activities that bring team members together. The literature indicates various techniques that have been applied to control the coordination level among team members. Notable among these techniques is social-technical congruence (STC), which helps to measure the alignment between the social and technical capabilities of an organization and teams at various stages of software development. The dynamic nature and changes of coordination requirements make STC a potential research area in this regard. The main objective of this study is to perform a systematic literature review (SLR) that recognizes and structures existing studies that represent new evolutionary trends in the field of STC. A SLR is performed of 46 publications from 4 data sources, including journals, conferences and workshop proceedings, most of which were published between 2008 and 2019. To this end, a thorough analysis is carried out to elicit the studies based on 7 research questions in this SLR. The outcome of this SLR is a set of ample research studies representing various aspects, performance impacts, factors, and evolutionary trends in the field of STC. Furthermore, STC measurement techniques are classified in two distinct groups, matrix based and social network analysis-based measures. After a systematic exploration of these aspects, this study results in new insightful features and state of art of STC. This SLR concludes that some areas still require further investigation. For instance, (1) STC-related literature exists, but only one research work mainly focuses on the risk of overwhelming STC (i.e., excessive STC measurement may overburden the software development process); (2) STC measurement techniques facilitate the identification of congruence gaps, but no attention has been given towards the unweighted social network analysis based STC measurement models; (3) STC measurement techniques are generally applied in the development phase of the project lifecycle, but these measurements are rarely used in other software development phases, such as the requirement and testing phases or all phases; and (4) The development factors that effects on STC measurement are rarely focused by researchers in the context of various domains.

Using Bibliometric Analysis to Measure and Understand the Gender Gap in Published Computing Books

2021 ◽  
Vol 13 (1) ◽  
pp. 31-44
Author(s):  
Arbana Kadriu ◽  
Kosovare Sahatqija ◽  
Lejla Abazi-Bexheti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Computer Science ◽  
Bibliometric Analysis ◽  
Gender Gap ◽  
Keyword Extraction ◽  
Content Learning ◽  
Female Authors ◽  
Analysis Methods

The purpose of the research presented in this paper is the investigation of the gender gap in published computing books. The book titles from the DBLP computer science bibliography were the basis for this investigation. The conducted research involves co-authorship network exploration using social network analysis methods, as well as content learning by keyword extraction and ranking from book titles. The findings show that female authors tend to publish fewer books in computing than their male colleagues, and there is a huge gap of women regarding the collaboration. There are just two women names within the 50 author names with the highest social network top metrics, indicating collaboration. Regarding the extracted keywords, though there are differences, results do not show some huge divergences when it comes to the used language for computing titles.

Bibliometric study of social network analysis literature

2019 ◽  
Vol 38 (2) ◽  
pp. 420-433 ◽  
Author(s):  
Yu-Sheng Su ◽  
Chien-Linag Lin ◽  
Shih-Yeh Chen ◽  
Chin-Feng Lai
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Bibliometric Analysis ◽  
Computer Mediated Communication ◽  
Content Type ◽  
Productivity Distribution ◽  
Author Productivity ◽  
Subject Areas ◽  
Lotka’S Law

Purpose The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas. Design/methodology/approach Bibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future. Findings It appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law. Research limitations/implications First, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation. Originality/value This research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA.

Social Network Analysis in Software Development Projects: A Systematic Literature Review

2020 ◽  
Vol 30 (03) ◽  
pp. 321-362
Author(s):  
Roland Robert Schreiber ◽  
Matthäus Paul Zylka
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Literature Review ◽  
Software Development ◽  
Systematic Literature Review ◽  
Project Teams ◽  
Development Projects ◽  
Project Organization

Software development in project teams has become more and more complex, with increasing demands for information and decision making. Software development in projects also hugely depends on effective interaction between people, and human factors have been identified as key to successful software projects. Especially in this context, managing and analyzing social networks is highly important. The instrument of social network analysis (SNA) provides fine-grained methods for analyzing social networks in project teams, going beyond the traditional tools and techniques of project management. This paper examines the importance of the application of SNA in software development projects. We conducted a systematic literature review (SLR) of research on software development projects and social network data published between 1980 and 2019. We identified and analyzed 86 relevant studies, finding that research on software development projects spans the topics of project organization, communication management, knowledge management, version and configuration management, requirement management, and risk management. Further, we show that most studies focus on project organization and that the most common method used to gather social data relies on automated extraction from various software development repositories in the SNA context. Our paper contributes to the software development literature by providing a broad overview of published studies on the use of social networks in helping software development projects. Finally, we identify research opportunities and make suggestions for addressing existing research gaps.

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