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

Authors

Michael Muller
Shion Guha PhD, Parkview HealthFollow
David Mimno
N. Sadat Shami

Abstract

GROUP '16: Proceedings of the 2016 ACM International Conference on Supporting Group Work.

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.

Document Type

Conference Proceeding

Publication Date

11-2016

First Page

3

Last Page

8

Comments

https://doi.org/10.1145/2957276.2957280

Recommended Citation

Muller, Michael; Guha, Shion PhD; Mimno, David; and Shami, N. Sadat, "Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination" (2016). Health Services and Informatics Research. 162.
https://researchrepository.parkviewhealth.org/informatics/162