Quantitative insights from online qualitative data: An example from the health care sector

In this study, IBM Watson is used to examine how knee replacement patients talk about their emotions and express sentiment through their comments online. Then, a latent class cluster modeling procedure is used to segment these patients into distinct groups, according to their emotions (anger, disgust, fear, happiness, sadness, and surprise), sentiment, and their overall satisfaction with knee replacement surgery. The findings show how qualitative online data can be transformed into quantitative insights regarding underlying market segments, which could then be targeted through different strategies by both marketers and health care practitioners.
Source: Psychology and Marketing - Category: Psychiatry & Psychology Authors: Tags: RESEARCH ARTICLE Source Type: research