An Empirical Study of Bioinformatics Topics in Online Forum Discussions

Abstract

In this paper, we aim to understand the topics discussed by bioinformatics practitioners in Stack Exchange sites. We downloaded all bioinformatics posts (questions and accepted answers) from four Stack Exchange Q&A sites (Stack Overflow, Biology, Cross-Validated, and Bioinformatics). Then we applied topic modeling on each site data. We labeled the topics and grouped those into high level categories. We analyzed the topics further by determining their popularity, difficulty, and evolution. We have made a comparative analysis of the topics across the different studied sites. We found 14 topics in Stack Overflow that are grouped into six categories. The number of new bioinformatics questions is steadily increasing over time in Stack Overflow for each topic category. Topics related to sequence analysis and pattern detection are the most popular as well as the most difficult to get an accepted answer. Most of the discussion posts are ‘how’ type questions, i.e., the practitioners were looking for solutions. While topics like biodata processing are found in multiple Stack Exchange sites, other topics (e.g., gene evolution analysis) are found in specialized sites (e.g., Biology). These findings show the need for consulting multiple related sites in Stack Exchange to learn interdisciplinary fields like bioinformatics. The tradeoff between popularity and difficulty of the bioinformatics topics highlights that bioinformatics practitioners need documentation and better tool support. The bioinformatics researchers, organizations, and practitioners can look into our results to prioritize the specific areas that need more focus for improvement.