ENHANCING USER EXPERIENCE THROUGH SENTIMENT ANALYSIS FOR KATSINA STATE TRANSPORT AGENCY: A TEXTBLOB APPROACH

Abstract

Katsina State Transport Authority is the state's government-owned transportation provider, operating in all local governments. Because of its extensive reach, it faces a difficult problem in measuring customer satisfaction with the services it delivers. The purpose of this research is to improve the experiences of Katsina State Transport Authority users by using sentiment analysis and the TextBlob library to categorize comments as neutral, negative, or positive. The study begins with meticulous data collecting using Google Forms to provide a representative sample that captures an all-encompassing view of user opinions. The study used feature engineering and model fine-tuning to improve the process, tailoring TextBlob's performance to the complexities of transportation-related feedback. The results reveal that 71% of respondents are usually happy with the agency's services, while 9% offered negative comments with ideas for improvement. This study's findings, which included sentiment analysis and topic modeling, present a road map for enhancing services and planning.