The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools
This work provides a framework for researchers and practitioners to evaluate SNA technologies, though it is incremental as it builds on existing literature and metrics.
The paper tackles the need for systematic evaluation in social network analysis (SNA) by proposing four dimensions and new metrics to assess SNA software tools, resulting in a quantitative analysis and ranking of 20 tools.
Social network based applications have experienced exponential growth in recent years. One of the reasons for this rise is that this application domain offers a particularly fertile place to test and develop the most advanced computational techniques to extract valuable information from the Web. The main contribution of this work is three-fold: (1) we provide an up-to-date literature review of the state of the art on social network analysis (SNA);(2) we propose a set of new metrics based on four essential features (or dimensions) in SNA; (3) finally, we provide a quantitative analysis of a set of popular SNA tools and frameworks. We have also performed a scientometric study to detect the most active research areas and application domains in this area. This work proposes the definition of four different dimensions, namely Pattern & Knowledge discovery, Information Fusion & Integration, Scalability, and Visualization, which are used to define a set of new metrics (termed degrees) in order to evaluate the different software tools and frameworks of SNA (a set of 20 SNA-software tools are analyzed and ranked following previous metrics). These dimensions, together with the defined degrees, allow evaluating and measure the maturity of social network technologies, looking for both a quantitative assessment of them, as to shed light to the challenges and future trends in this active area.