A Study of FOSS'2013 Survey Data Using Clustering Techniques
This work provides insights into FOSS communities, especially regarding gender representation, but is incremental as it applies existing methods to a specific dataset.
The study analyzed the FOSS 2013 survey dataset using clustering techniques like multiple correspondence analysis to uncover hidden trends, particularly focusing on women contributors, and drew important inferences about development practices in free and open-source software.
FOSS is an acronym for Free and Open Source Software. The FOSS 2013 survey primarily targets FOSS contributors and relevant anonymized dataset is publicly available under CC by SA license. In this study, the dataset is analyzed from a critical perspective using statistical and clustering techniques (especially multiple correspondence analysis) with a strong focus on women contributors towards discovering hidden trends and facts. Important inferences are drawn about development practices and other facets of the free software and OSS worlds.