Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination

Muller, M., Guha, S., Baumer, E.P.S., Mimno, D., and Shami, N.S. (2016). Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination. in Proceedings of the ACM Conference on Supporting Group Work (GROUP). (Sanibel Island, FL).

Abstract

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.

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