Sentiment analysis or opinion mining is a field of study that analyzes people's sentiments, attitudes, or emotions towards certain entities. This project tackles a fundamental problem of sentiment analysis, sentiment polarity categorization. Online product reviews from Amazon are selected as data used for this study. A sentiment polarity categorization process has been proposed along with detailed descriptions of each step. Experiments for both sentence-level categorization and review-level categorization have been performed.
Sentiment analysis tools can be used by organizations for a variety of application, including:
- Identifying brand awareness, reputation and popularity at a specific moment or over time.
- Tracking consumer reception of new products or features.
- Evaluating the success of marketing campaign.
- Pinpointing the target audience or demographics.
- Collecting customer feedback from social media, websites or online forms.
- Conducting market research.
- Categorizing customer service requests.
Contributions are what make the GitHub community such an amazing place to learn, inspire, and create. These are all the members that have directly contributed towards the completion of this project.
| Vishal Kumar Shaw |  |
|---|---|
| Sneha Shaw | |
| Masud Gazi | |
| Gurjot Singh | |
| Deepsagar Boral | |
Distributed under the MIT License. See LICENSE.md for more information.
Avinaba Bera
