Publications
Publications
- August 2017 (Revised December 2018)
- HBS Case Collection
Tamarin App: Natural Language Processing
By: Srikant M. Datar and Caitlin N. Bowler
Abstract
In this case, students explore the challenges of using sentiment analysis to monitor and understand public perception around a software application, Tamarin SEO App. Technical topics include building a filtering classifier using naive Bayes and sentiment analysis This case was written for the second-year MBA course “Managing with Data Science.” The course provides MBA students with no programming experience an introduction to the field of data science and its applications in business. Students learn to (1) carefully articulate the business ask, (2) reason carefully from the ask; through metrics and models, and outputs; and (3) evaluate outputs from models to (4) develop a plan for action.
Keywords
Data Science; Branding; Data Analytics; Analytics and Data Science; Brands and Branding; Analysis; Perception; Planning
Citation
Datar, Srikant M., and Caitlin N. Bowler. "Tamarin App: Natural Language Processing." Harvard Business School Case 118-015, August 2017. (Revised December 2018.)