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The four dimensions of social network analysis: An overview of research methods, applications, and software tools.
- Source :
-
Information Fusion . Nov2020, Vol. 63, p88-120. 33p. - Publication Year :
- 2020
-
Abstract
- • Up-to-date literature review of basic research and application domains in social networks. • Definition of a new set of metrics to measure the capacity of SNA frameworks and tools. • Quantitative analysis of social network analysis tools and frameworks (SNA). • Evaluation of 20 popular SNA software tools according to the new set of metrics. • SNA software technology assessment. 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15662535
- Volume :
- 63
- Database :
- Academic Search Index
- Journal :
- Information Fusion
- Publication Type :
- Academic Journal
- Accession number :
- 145698738
- Full Text :
- https://doi.org/10.1016/j.inffus.2020.05.009