An analysis of top author citations in software engineering and a comparison with other fields

• Published in: Scientometrics Vol. 126; no. 11; pp. 9147 - 9183
• Main Authors: Petersen, Kai, Ali, Nauman Bin
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01-11-2021; Springer Nature B.V
• Subjects: Author citations; Citation analysis; Comparison; Computer programs; Computer Science; Information Storage and Retrieval; Library Science; Self-citations; Software; Software engineering; Statistical analysis; Self-citations; Author citations; Comparison; Software engineering
• ISSN: 0138-9130; 1588-2861; 1588-2861
• DOI: 10.1007/s11192-021-04144-1

Ioannidis et al. provided a science-wide database of author citations. The data offers an opportunity to researchers in a field to compare the citation behavior of their field with others. In this paper, we conduct a systematic analysis of citations describing the situation in software engineering and compare it with the fields included in the data provided by Ioannidis et al. For comparison, we take the measures used by Ioannidis into consideration. We also report the top-scientists and investigate software engineering researchers’ activities in other fields. The data was obtained and provided by Ioannidis et al. based on the Scopus database. Our method for analysis focuses on descriptive statistics. We compared software engineering with other fields and reported demographic information for the top authors. The analysis was done without any modifications to the ranking. In the later analysis, we observed that 37% of researchers listed as software engineers were not in the software engineering field. On the other hand, the database included a large portion of top authors (ca. 60% to 80%) identified in other software engineering rankings. Other fields using the database are advised to review the author lists for their fields. Our research’s main risk was that researchers are listed that do not belong to our studied field.