The Review Subjectivity Dataset is a collection of Amazon product reviews, spanning various product types. The dataset aims to analyze the subjectivity of customer reviews, which is crucial for understanding customer sentiment and improving product recommendations.
- Sentiment Analysis: The dataset provides a rich source for sentiment analysis, helping businesses understand customer emotions and opinions.
- Product Improvement: By analyzing review subjectivity, companies can identify areas for product improvement and tailor their offerings to meet customer needs.
- Customer Insights: Understanding the subjectivity of reviews can offer deeper insights into customer preferences and behavior.
The dataset is creatively compiled to include a diverse range of product types, ensuring a comprehensive analysis of review subjectivity across different categories.
- Deep Learning.ipynb: Demonstrates the use of deep learning techniques to build models for subjectivity analysis.
- Machine Learning Methods.ipynb: Explores various machine learning methods for modeling and analyzing review subjectivity.
- Clone the repository to your local machine.
- Explore the notebooks to understand the modeling approaches.
- Use the dataset for your research or projects in sentiment analysis and customer behavior.
Contributions to enhance the dataset or improve the modeling techniques are welcome. Please feel free to submit pull requests or open issues to discuss potential improvements.
Email: [email protected]
Happy Analyzing!