https://github.com/harmanveer-2546/sentiment-analysis-of-amazon-fine-food

For this project, machine learning algorithms are used on amazon fine food reviews dataset to analyze if the given review is a positive review or a negative review.
https://github.com/harmanveer-2546/sentiment-analysis-of-amazon-fine-food

mathplotlib nlp-machine-learning ntlk numpy pandas pipeline python roberta-model seaborn transformer vader-sentiment-analysis

Last synced: 6 days ago
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For this project, machine learning algorithms are used on amazon fine food reviews dataset to analyze if the given review is a positive review or a negative review.

• Host: GitHub
• URL: https://github.com/harmanveer-2546/sentiment-analysis-of-amazon-fine-food
• Owner: harmanveer-2546
• Created: 2024-05-28T09:25:14.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-05-28T09:29:47.000Z (6 months ago)
• Last Synced: 2024-05-30T17:37:51.124Z (6 months ago)
• Topics: mathplotlib, nlp-machine-learning, ntlk, numpy, pandas, pipeline, python, roberta-model, seaborn, transformer, vader-sentiment-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 1.46 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Sentiment Analysis of Amazon Fine Food

The modernized world with recent inventions in technology seen nowadays has become more digitized. By making the products available online, e-commerce is taking advantage of this digitized world by making the customers get whatever they want without stepping out. The importance of the online review has become higher these days because the number of people depending on e-commerce websites for purchasing things have increased. As people believe in other opinions, going through lots of reviews before buying a product has become a common thing. For a better understanding of the product, in this busy world people don't have time to go through lots of, so, there is a need for developing a model which can polarize those reviews and generate an appropriate result. With the advancement in the area of machine learning and different technology, this task has become much more comfortable. 

This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.

#### Data includes:

Reviews from Oct 1999 - Oct 2012


568,454 reviews


256,059 users


74,258 products


260 users with > 50 reviews