AmaProductReviews 0.0.6

Analyze Amazon product reviews

Project Description: Amazon Product Review Analysis

This Python script aims to analyze Amazon product reviews by extracting reviews from a specific product's URL and performing sentiment analysis on those reviews.

Functions Overview:

1. get_url_review_page(UrlProduct, i):

   • Constructs the URL for a specific page of product reviews.

2. get_rating(UrlProduct):

   • Retrieves the overall rating of the product.

3. get_product_name(UrlProduct):

   • Extracts the name of the product from its URL.

4. get_global_rating(UrlProduct):

   • Fetches the global rating of the product.

5. get_image_url(UrlProduct):

   • Obtains the URL of the product's image.

6. extract_reviews(UrlProduct):

   • Extracts reviews from a specific page of product reviews.

7. extract_all_reviews(UrlProduct):

   • Extracts all reviews from multiple pages of product reviews.

8. clean_comment(comment):

   • Cleans the text of a comment by converting it to lowercase, removing non-alphabetic characters, digits, and stop words.

9. sentiment_analysis_textblob(text):

   • Performs sentiment analysis using TextBlob and returns the sentiment label (Positive, Negative, or Neutral).

10. comment_dataFrame(UrlProduct):

    • Constructs a DataFrame containing cleaned comments and their corresponding sentiments.

11. sentiment_by_comment(df):

    • Calculates the count of comments by sentiment.

Installation Requirements:

• Python 3.x
• Packages listed in the requirements.txt file. Install them using pip install -r requirements.txt.
• en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl#sha256=86cc141f63942d4b2c5fcee06630fd6f904788d2f0ab005cce45aadb8fb73889
• beautifulsoup4
• selenium
• pandas
• nltk
• spacy
• textblob
• streamlit
• plotly
• requests
• wordcloud
• webdriver_manager

Team Members:

• El Ouankrimi Ali
• Olamine Zakaria
• Oubella Abdallah