The Development of Social Network Analysis

Social Network Analysis 26.2 Visualization Principles Illustrative Example Substance, Design, Algorithm 26.3 Substance-based Designs Prominence Cohesion Two-mode networks Dynamics 26.4 Trends and Challenges Social networks provide a rich source of graph drawing problems, because they appear in an incredibly wide variety of forms and contexts. After sketching the scope of social network analysis, we establish some general principles for social network visualization before nally reviewing applications of, and challenges for, graph drawing methods in this area. Other accounts more generally relating to the status of visualization in social network analysis are given, e.g., in [Klo81, BKR+99, Fre00, Fre05,

BKR06]. Surveys that are more comprehensive on information visualization approaches, interaction, and network applications from social media are given in [CM11, RF10, CY10]. 26.1 Social Network Analysis The fundamental assumption underlying social network theory is the idea that seemingly autonomous individuals and organizations are in fact embedded in social relations and interactions [BMBL09]. The term social network was coined to delineate the relational perspective from other research traditions on social groups and social categories [Bar54]. In general, a social network consists of actors (e.g., persons, organizations) and some form of (often, but not necessarily: social) relation among them. The network structure is usually modeled as a graph, in which vertices represent actors, and edges represent ties, i.e., the existence of a relation between two actors. Since traits of actors and ties may be important, both vertices and edges can have a multitude of attributes. We will use graph terminology for everything relating to the data model, and social network terminology when referring to substantive aspects. While attributed graph models are indeed at the heart of formal treatments, it is worth noting that theoretically justi ed data models are not as obvious as it may seem [But09]. In fact, social network analysis is maturing into a paradigm of distinct structural theories and associated relational methods. General introductions and methodological overviews can be found in [WB88, WF94, Sco00, CSW05, BE05], a historic account in [Fre04a], and a comprehensive collection of in uential articles in [Fre08]. c 2005 by CRC Press Figure 26.1 A sociogram from [Mor53, p. 422] showing a graph with fourteen highlighted vertices and four clusters. In social network reseach it is important to clarify whether the networks are considered dependent or explanatory variables. In the former case the interest is in why and how networks form the way they do, and in the latter case the interest is in why and how networks in uence other outcomes. For convenience, we will refer to the former as network theory (studying network formation) and to the latter as network analysis (studying network e ects). A major distinction from non-network approaches is that the unit of analysis is the dyad, i.e. a pair of actors (may they be linked or not) rather than a monad (a singleton actor). The methodological toolbox can be organized into the following main compartments. Indexing The assignment of values to predetermined substructures of any size. Most common...

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