Research Details

Abstract

Sentiment analysis, which lies at the intersection of computer science and linguistics, uses machine learning and natural language processing in an attempt to identify and categorize the emotions underpinning language captured in digital records such as product reviews, chat logs, and social media. At its most basic, sentiment analysis is used to define a reaction as either positive, negative, or neutral. This task is complicated by the complexity of human expression, but used effectively it can help businesses gauge how consumers feel about a product or service, track trends, and explore new market opportunities. This case reviews the history, benefits, and limitations of using sentiment analysis successfully in business contexts.

Type

Case

Author(s)

Sara Owsley Sood, Theo Anderson

Date Published

08/25/2021

Citations

Sood, Sara Owsley, and Theo Anderson. Tell Us How You Really Feel: Capturing the Market Value of Emotions through Sentiment Analysis. Case 5-321-503.