Abstract: 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. This talk will describe our latest work on SNA applications and frameworks. This keynote provides a introduction to our research published recently by Information Fusion journal [1] (freely available at arxiv.org [2]), where a new way to assess the maturity of technology related to SNA is proposed and supported by the definition of four different dimensions, namely: 1) Pattern & Knowledge discovery, 2) Information Fusion & Integration, 3) Scalability, and 4) 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 analysed 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. The talk will provide the empirical results on that evaluations, and a GitHub open repository where researchers, practitioners, or anyone interested in SNA technology are invited to contribute.

Related references

• David Camacho, Angel Panizo-LLedot, Gema Bello-Orgaz, Antonio Gonzalez-Pardo, and Erik Cambria. "The four dimensions of social network analysis: An overview of research methods, applications, and software tools". Information Fusion, 63:1–33, 2020.
• David Camacho, Ángel Panizo-LLedot, Gema Bello Orgaz, Antonio González-Pardo, Erik Cambria: "The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools". CoRR abs/2002.09485 (2020)

Biographical note: David Camacho is currently working as Full Professor with the Departamento de Sistemas Informáticos (Computer Systems Engineering Department) at Universidad Politécnica de Madrid (Spain), and leads the Applied Intelligence and Data Analysis group (AIDA). He received a PhD in Computer Science (2001) from Universidad Carlos III de Madrid, and a B.S. in Physics (1994) from Universidad Complutense de Madrid. He has published more than 300 research papers, and his research interests include Data Mining, Evolutionary Computation, Social Network Analysis, and Swarm Intelligence, among others. He is on the editorial board of several journals, such as Information Fusion, Journal of Ambient Intelligence & Humanized Computing, International Journal of Bioinspired Computation, or Expert systems. Contact him at: david.camacho@upm.es.