Author Abstract
This method survey article covers natural language processing methods focused on text analytics, and machine learning methods and their applications to management research. The methods are presented accessibly with directly applicable examples, supplemented by a rich set of references crossing multiple sub-fields of management science. Methods covered include vector space models, similarity, sentiment analysis, classification, decision trees, boosting and cross-validation, k-means, and k-nearest-neighbors. The intended audience is the strategy and management researcher with an interest in understanding concepts and applications of machine learning for strategy research.
Paper Information
- Full Working Paper Text
- Working Paper Publication Date: July 2017
- HBS Working Paper Number: HBS Working Paper #18-011
- Faculty Unit(s): Strategy