Analyze Amazon product reviews
Project description
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:
-
get_url_review_page(UrlProduct, i):
- Constructs the URL for a specific page of product reviews.
-
get_rating(UrlProduct):
- Retrieves the overall rating of the product.
-
get_product_name(UrlProduct):
- Extracts the name of the product from its URL.
-
get_global_rating(UrlProduct):
- Fetches the global rating of the product.
-
get_image_url(UrlProduct):
- Obtains the URL of the product's image.
-
extract_reviews(UrlProduct):
- Extracts reviews from a specific page of product reviews.
-
extract_all_reviews(UrlProduct):
- Extracts all reviews from multiple pages of product reviews.
-
clean_comment(comment):
- Cleans the text of a comment by converting it to lowercase, removing non-alphabetic characters, digits, and stop words.
-
sentiment_analysis_textblob(text):
- Performs sentiment analysis using TextBlob and returns the sentiment label (Positive, Negative, or Neutral).
-
comment_dataFrame(UrlProduct):
- Constructs a DataFrame containing cleaned comments and their corresponding sentiments.
-
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 usingpip 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 #\x00 \x00A\x00m\x00a\x00P\x00r\x00o\x00d\x00u\x00c\x00t\x00R\x00e\x00v\x00i\x00e\x00w\x00s\x00 \x00 \x00
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