Skip to content

README.md

Latest commit

 

History

History
49 lines (34 loc) · 1.57 KB

README.md

File metadata and controls

49 lines (34 loc) · 1.57 KB

Sentiment Analysis of Customer Reviews

A Python program for analyzing customer reviews to classify sentiments (Positive, Negative, Neutral) and extract recurring themes. This project was created as part of the CSSD 601: Advanced Computation and Programming Using Python course at Ghana Communication Technology University (GCTU).

Assignment Details

Institution: Ghana Communication Technology University (GCTU)
Faculty: Faculty of Computing and Information Systems (FoCIS)
Department: Computer Science (CS)
Program: MSc/MPhil Computer Science
Course: CSSD 601 - Advanced Computation and Programming Using Python
Assessment: Application of Python Programming Assessment

Features

  • Perform sentiment analysis on customer reviews.
  • Generate a summary of sentiment distribution.
  • Extract recurring themes using word clouds.

Installation

  1. Clone this in a jupyter notebook terminal: 
    git clone https://github.com/sahadevgh/sentiment-analysis.git

Usage

  1. Use the available dataset for testing (e.g., reviews.csv), or Place your own dataset in the project folder.
  2. The dataset contains customer reviews in a single column labeled review. Replace the sample dataset with your own for custom analysis.
  3. Run the cell with the main code: 
    sentiment_analysis.ipynb
  4. View the output, including sentiment distribution and word cloud visualizations.

Results

  • Sentiment Distribution: Visualized as a bar chart.
  • Recurring Themes: Highlighted in a word cloud.