Graph Theory, Social Network Analysis, and Network Science
Network analysis provides a versatile framework for modeling complex systems and because of its universal applicability it has been invented and rediscovered in many different disciplines. Each of these disciplines enriches the field by providing its own
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Graph Theory, Social Network Analysis, and Network Science
Abstract Network analysis provides a versatile framework for modeling complex systems and because of its universal applicability it has been invented and rediscovered in many different disciplines. Each of these disciplines enriches the field by providing its own perspective and its own approaches; the three most prominent disciplines in the area are sociology, graph theory, and statistical physics. As these disciplines follow very different aims, it is vital to understand the different approaches and perspectives. This chapter elaborates and opposes the different approaches to highlight those points which are important for the topic of interest—network analysis literacy.
2.1 Introduction This chapter will introduce the main perspectives of the fields that are at the core of complex network analysis: graph theory, sociology, and physics. The combination of these fields, their different publication strategies, their views on how to do science make it more difficult to develop a literacy of the set of methods than in other fields. Thus, this chapter starts with a discussion of the views of these three fields (and quickly sketches the perspectives of other fields) in Sect. 2.2. The main difference in perspective between sociology and physics, leading to different problems, is then highlighted in Sect. 2.3. Section 2.4 shows why this evolution of the field creates problems and what general requirements are needed to make network analysis a principled field with guidelines on when to use which measure. This section borrows heavily from similar arguments in statistics, which experiences similar problems: many domain experts that use methods from a tool set that are implemented in software packages and a long history of almost “ritually” applying certain methods. The chapter is closed by a collection of recommend readings in Sect. 2.5.
© Springer-Verlag GmbH Austria 2016 K.A. Zweig, Network Analysis Literacy, Lecture Notes in Social Networks, DOI 10.1007/978-3-7091-0741-6_2
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2 Graph Theory, Social Network Analysis, and Network Science
2.2 The Basis Getting into the field of network analysis is quite an endeavor as there are so many different terms describing it. Some projects are categorized as being from a field called social network analysis, others are from complex network analysis, network science, or network theory, or finally from the field of graph theory. So, are these terms synonyms describing the same field of study or what is their connection? This book is mainly concerned with complex network analysis, a part of a new field christened network science or network theory by one of its most prominent founders, Albert-László Barabási. Complex network analysis uses many approaches and methods from a field called social network analysis, which originated in sociology and is itself based on theorems and algorithms from graph theory (s. Fig. 2.1). The following paragraphs present a short overview of the most important questions and approaches in ea
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