Project Title: Sentiment Analysis of Customer Review Datasets
Teammates Name:
- Abhilasha Jagtap
- Jeeva Saravana Bhavanandam
- Madhurya Shankar
- Sahithi Sane
- Sandhya Kilari
Problem Statement:
Sentiment analysis, commonly referred to as opinion mining, constitutes a pivotal undertaking within the field of Natural Language Processing (NLP), entailing the precise classification of sentiment conveyed within textual data into positive, negative, or neutral categories. Customer reviews play a crucial part in anything from purchasing a product to visiting a location. The primary objective of this master's project is to embark on the creation of a comprehensive and sophisticated sentiment analysis system, meticulously engineered to autonomously discern and categorize sentiment within diverse customer review datasets.
Broader Impact: Sentiment analysis is That being stated, this can also serve as a foundation for a Product Recommendation System and Fake Review and opinion Spam Detection.
By undertaking this project, we aim to contribute to the advancement of sentiment analysis, providing a sophisticated and adaptable tool that can be applied across various industries commonly used in reviews and survey answers, online and social media, and healthcare materials for uses ranging from marketing to customer service to clinical medicine. to extract valuable insights from customer reviews.
Dataset:
The project seeks to design and implement a sentiment analysis system that can analyze customer reviews from different sources, such as e-commerce websites, social media platforms, or product review forums.
Google Review Dataset - https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/googlelocal/