Application of Convolutional Neural Network Algorithm in Sentiment Analysis for Evaluating Customer Satisfaction. A Case Study for Mobile and Fixed Internet Service Providers in Zimbabwe
- Author
- Tapera, Praise
- Title
-
Application of Convolutional Neural Network Algorithm in Sentiment Analysis for Evaluating Customer Satisfaction. A Case Study for Mobile and Fixed Internet Service Providers in Zimbabwe
- Abstract
- This research topic aims to evaluate customer satisfaction using sentiment analysis for mobile and fixed internet service providers in Zimbabwe. The study is significant because it recognizes the growing importance of customer satisfaction in the telecommunications industry and the need to measure it systematically and continuously. The research methodology will involve collecting data through surveys and sentiment analysis tools and analyzing the data using statistical and sentiment analysis techniques. The expected outcomes of the study include providing insights into the factors that influence customer satisfaction in the mobile and fixed internet service providers in Zimbabwe, evaluating the effectiveness of sentiment analysis in measuring customer satisfaction, and proposing recommendations for improving customer satisfaction in the telecommunications industry in Zimbabwe. The study's relevance to the mobile and fixed internet service industry in Zimbabwe lies in its potential to provide a systematic and objective way of measuring customer satisfaction and identifying areas for improvement, ultimately leading to long-term profitability and success.
- Date
- 2023
- Publisher
- BUSE
- Keywords
- Convolutional Neural Network Algorithm
- Sentiment Analysis
- Evaluating Customer Satisfaction
- Mobile and Fixed Internet Service Providers
- Supervisor
- Mr Matombo
- Item sets
- Department of Computer Science
