Visualization of Ranking Authors Based on Social Networks Analysis and Bibliometrics

Abstract

It is interesting to rank scientists in a specific field, which would help researchers to know about the research status of the field and gain valuable insight on future technical trends in the field. Our paper visualizes the results of author ranking with the consideration of authors’ contribution. In this paper, every author’s contribution to his/her field is calculated according to the co-authorship among papers. By extracting the papers and authors information from a field since they started publication, the co-author network are constructed. We also get the clusters partition of those authors by Girvan-Newman algorithm. For conducting detailed experiments to show the visualized our results, we select the field of Intelligent transportation system (ITS) as an example. Since thousands of papers were published by scientists each year in the ITS field, academic co-authorship in this field expands fast. We design our dataset composed by data from four journals in the ITS field to visualize our algorithm.