Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination
Association for Computing Machinery (ACM)
Proceedings of the 19th International Conference on Supporting Group Work (GROUP '16)
Grounded Theory Method (GTM) and Machine Learning (ML) are often considered to be quite different. In this note, we explore unexpected convergences between these methods. We propose new research directions that can further clarify the relationships between these methods, and that can use those relationships to strengthen our ability to describe our phenomena and develop stronger hybrid theories.
Muller, Michael; Guha, Shion; Baumer, Eric P.S.; Mimno, David; and Shami, N. Sadat, "Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination" (2016). Mathematics, Statistics and Computer Science Faculty Research and Publications. 515.