Time: 18th,June.15：00pm-16:30pm
About Lecture：In bibliometrics, there are two main procedures to explore a research field: performance analysis and science mapping. Performance analysis aims at evaluating groups of scientific actors (countries, universities, departments, researchers) and the impact of their activity on the basis of bibliographic data. Science mapping aims at displaying the structural and dynamic aspects of scientific research, delimiting a research field, and quantifying and visualizing the detected subfields by means of co-word analysis or documents co-citation analysis. In this talk we present two bibliometric tools that we have developed in our research laboratory SECABA: H-Classics to develop performance analysis by based on Highly Cited Papers and SciMAT to develop science mapping guided by performance bibliometric indicators.
About Lecturer：Enrique Herrera-Viedma is Professor in Computer Science and Artificial Intelligence in University of Granada (UGR) and currently, Vice-President for Research and Knowlegde Transfer. His current research interests include group decision making, consensus models, linguistic modeling, aggregation, information retrieval, bibliometrics, digital libraries, web quality evaluation, recommender systems, blockchain and social media. In these topics he has published more than 300 papers in ISI journals, coordinated more than 25 research projects, and received more than 35.000 citations according to Web of Science, being his h-index 83 and 101 in Google Scholar .
(https://scholar.google.com/citations?user=g8ZXTuYAAAAJ&hl=es).
Dr.Herrera-Viedma was Vice-President Publications in IEEE SMC Society during 2019-2020, now he is VP Cybernetics in IEEE SMC Society, he is IEEE FELLOW and IFSA Fellow from 2021 and Associate Editor of international journals such as the IEEE Trans. On Syst. Man, and Cyb.: Systems, IEEE Trans. On Fuzzy Systems, IEEE Trans. On Cybernetics, Knowledge Based Systems, Soft Computing, Fuzzy Optimization and Decision Making, Applied Soft Computing, Journal of Intelligent and Fuzzy Systems, and Information Sciences. He is identified by Clarivate Analytics as HIGHLY CITED RESEARCHER in Computer Science and Engineering from 2014 to 2020 in both categories, “Computer Science” and “Engineering”.
