The web has changed how people collaborate, communicate and express opinions and sentiments. Opinion Mining (OM) is popular due to the quick growth of web users, increasing online discussion forums and social media sites. OM determines feelings/opinions of others about services, products, politics and policies. There are huge unstructured, free-text information about health care quality available on the net from social networks, blogs and health-care rating websites. When sentiment analysis is applied to health care, it reveals a new approach to analyse huge volumes of textual information about patient’s experiences to locate patterns and understand data. This paper proposes an OM system dimensionality reduction technique to mine user generated health reviews. The new method classifies patient reviews from online forums as positive/negative automatically. Results show the new dimensionality reduction techniques efficiency in classifying.
|Number of pages||6|
|Journal||Intelligent Automation and Soft Computing|
|Publication status||Published - 03-04-2017|
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computational Theory and Mathematics
- Artificial Intelligence