2020/02/21 by David Camacho, Camacho, David, Ángel Panizo-LLedot +7 · 1 citation
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Social and Information Networks (cs.SI) #Web visibility and informetrics
paper · pdf · doi:10.48550/arxiv.2002.09485
openalex publication_date 2020/02/21 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
Social network based applications have experienced exponential growth in\nrecent years. One of the reasons for this rise is that this application domain\noffers a particularly fertile place to test and develop the most advanced\ncomputational techniques to extract valuable information from the Web. The main\ncontribution of this work is three-fold: (1) we provide an up-to-date\nliterature review of the state of the art on social network analysis (SNA);(2)\nwe propose a set of new metrics based on four essential features (or\ndimensions) in SNA; (3) finally, we provide a quantitative analysis of a set of\npopular SNA tools and frameworks. We have also performed a scientometric study\nto detect the most active research areas and application domains in this area.\nThis work proposes the definition of four different dimensions, namely Pattern\n& Knowledge discovery, Information Fusion & Integration, Scalability, and\nVisualization, which are used to define a set of new metrics (termed degrees)\nin order to evaluate the different software tools and frameworks of SNA (a set\nof 20 SNA-software tools are analyzed and ranked following previous metrics).\nThese dimensions, together with the defined degrees, allow evaluating and\nmeasure the maturity of social network technologies, looking for both a\nquantitative assessment of them, as to shed light to the challenges and future\ntrends in this active area.\n