The-alpha-male/Starlink_customer_sentiment_analysis

The project conducts customer sentiment analysis on Starlink product reviews from Jumia Kenya by employing web scraping techniques to gather data from various pages. It processes the reviews to assess sentiment polarity, offering insights into customer opinions. The analysis showcases skills in data acquisition, natural language processing (NLP), a # Customer Sentiment Analysis on Starlink Reviews from Jumia Kenya ## Project Overview This project performs customer sentiment analysis on reviews for the Starlink product, sourced from Jumia Kenya. Click here to get the link. Using a web scraping approach, it extracts reviews from multiple pages and processes them to determine sentiment polarity, providing insights into customer opinions. This analysis demonstrates proficiency in data acquisition, natural language processing (NLP), and visualization. ## Features - Web Scraping: Collects customer reviews for a specified product from Jumia. - Sentiment Analysis: Implements sentiment analysis using multiple NLP techniques to assess customer sentiment. - Data Visualization: Visualizes sentiment distributions to communicate insights effectively. - CSV Export: Saves raw data and processed sentiments to a CSV file for further analysis. ## Installation 1. Clone the repository: ```github.com``` 2. Install dependencies: This project uses Python libraries such as `requests`, `BeautifulSoup`, `nltk`, `pandas`, and `matplotlib.` ```!pip install -r requirements.txt``` 3. Download NLTK data files: The project relies on NLTK's stopwords and sentiment lexicon, which need to be downloaded: ``` nltk.download('stopwords') nltk.download('vader_lexicon') nltk.download('punkt') ``` ## Usage 1. Run the Notebook: Open and execute the Jupyter Notebook Sentiment_Analysis.ipynb to perform the entire analysis. 2. Web Scraping: Modify the web scraping code to target specific products or pages. 3. Analyze Sentiments: The notebook walks through data processing, cleaning, and sentiment analysis steps. ## Project Structure ## Data Pipeline ### Web Scraping The project uses the requests library to fetch HTML content from Jumia’s product pages. `BeautifulSoup` extracts relevant review data, storing each review in a structured list. Data is fetched from multiple pages, as sho …