Degree
Master of Science in Data Science
Department
Department of Computer Science
Faculty/ School
School of Mathematics and Computer Science (SMCS)
Date of Submission
Spring 2023
Supervisor
Dr. Abdul Basit Shaikh, Visiting Faculty, Department of Computer Science, School of Mathematics and Computer Science (SMCS)
Keywords
Sentiment Analysis, Web Scraping, Data Science, Machine Learning, Natural Language Processing
Abstract
This project focuses on sentiment analysis and theme selection of negative reviews using natural language processing techniques. By leveraging web scraping, text preprocessing, machine learning algorithms, and topic modeling, the project aims to automate the analysis of negative reviews and provide valuable insights for businesses. The solution involves scraping data from online review platforms, preprocessing the text data, performing sentiment analysis using machine learning algorithms, and categorizing reviews into different topics using topic modeling techniques. The project code is implemented in Python, utilizing popular libraries such as pandas, numpy, scikit - learn, and nltk. The potential impact of this project lies in its ability to help businesses improve their products, services, and customer satisfaction by identifying common issues and sentiments expressed in negative reviews.
Document Type
Restricted Access
Submission Type
Research Project
Recommended Citation
Batla, M. (2023). Web Scraping and Sentiment Analysis of Foodpanda Reviews (Unpublished graduate research project). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/research-projects-msds/10
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