English

A Study of FOSS'2013 Survey Data Using Clustering Techniques

Artificial Intelligence 2017-02-01 v2 Computers and Society Software Engineering Machine Learning

Abstract

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.

Keywords

Cite

@article{arxiv.1701.08302,
  title  = {A Study of FOSS'2013 Survey Data Using Clustering Techniques},
  author = {Mani A and Rebeka Mukherjee},
  journal= {arXiv preprint arXiv:1701.08302},
  year   = {2017}
}

Comments

IEEE Women in Engineering Conference Paper: WIECON-ECE'2016 (Scheduled to appear in IEEE Xplore )

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