Citation and Topic Analysis of the ESEM Papers

Context: The pool of papers published in ESEM. Objective: To utilize citation analysis and automated topic analysis to characterize the SE research literature over the years focusing on those papers published in ESEM. Method: We collected data from Scopus database consisting of 513 ESEM papers. For thematic analysis, we used topic modeling to automatically generate the most probable topic distributions given the data. Results: Nearly 42% of the papers have not been cited at all but the effect seems to wear off as time passes. Using text mining of article titles and abstracts, we found that currently the most popular research topics in the ESEM community are: systematic reviews, testing, defects, cost estimation, and team work. Conclusions: While this study analyzes the paper pool of the ESEM symposium, the approach can easily be applied to any other sub-set of SE papers to conduct large scale studies. Due to large volumes of research in SE, we suggest using the automated analysis of bibliometrics as we have done in this paper.