Abstract
Customer satisfaction in the organization's services can play a crucial role in reforming their business strategy for better productivity. Some organizations measure their customer satisfaction through the percentage of happiness rate, some through non-systematic surveys, and some through direct interviews with their customers. Customers’ feedbacks can be gathered in two formats; structured data (numeric ratings) and unstructured data (comments). Being able to have a comprehensive measure of the quality of government services by considering those two formats makes it a big challenge to make useful insights from data for customers and decision-makers. The work in this paper analyzes customers' votes and feedbacks for using different government and private services in Dubai that were gathered from the Happiness Meter tool. The visualization of the quantitative information will be used to derive meaningful insights from data. Along with, natural language preprocessing techniques to develop a model that classifies comments based on strength and captures the insights and sentiment related to the user experience.
Publication Date
4-30-2020
Document Type
Master's Project
Student Type
Graduate
Degree Name
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research
Advisor
Ioannis Karamitsos
Recommended Citation
Alblooshi, Maitha Ahmed Hussain, "An Analysis of Happiness Meter Data through Data Mining Tools and Sentiment Classification" (2020). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/12223
Campus
RIT Dubai
