Visualizing Garfield’s Scientific Performance

Aim/Background: Garfield is one of the most important and influential figures in information science, bibliometrics and scientometrics. This paper aimed to investigate, analyze and visualize Garfield’s scientific outputs using the scientometrics technique. Materials and Methods: Data were gathered from the Web of Science core collection database by searching “Garfield E” based on which 1542 documents were extracted. Co-author analysis, co-citation analysis and also historiography techniques were used for data analysis. Some software such as HistCite, VOSviewer, Ucinet and NetDraw were also used for drawing the maps and analyzing data. The process of data analysis was conducted in three phases using three software. Results: The results showed 1542 written documents by Garfield indexed in WoS databases. As for word occurrence, “Science” and “Citation” were the most frequent ones. Most of these documents were published by CURRENT CONTENTS and Scientist publications. The highest number of products were observed in 1987 and 1988. The historiographical map of these documents were drawn for 1954 and 2004 and relevant clusters were formed. The co-citation map was also designed with clusters. Meanwhile, the co-author network was developed into a big cluster. According to the results of co-author analysis, Garfield mostly appeared as a co-author with Sher, Welljamsdorof and Pudovkin. The density of co-author network was 0.0679 in which Garfield with 133 and Sher and Reversz, each with 17 degrees, had the highest degree of co-authorship compared with other authors. Conclusion: The scientific maps provided by the present research, in line with those of the previous studies, support Garfield’s influence and role as one of the leading figures in the world of information science and scientometrics.