Sentiment Analysis for Better User Experience in Tourism Chatbot using LSTM and LLM
Ommi Balamurali, A.M. Abhishek Sai, Moturi Karthikeya, Sruthy Anand
Abstract
Emotions of human plays a vital role in the usage of any technical solutions. AI now provide various opportunity to devise solutions that can understand human emotion from written and spoken words. In this research, we focus on the importance and application of sentiment analysis for an AI chatbot designed for tourism. The chatbot helps to act as a real-time information service system for tourists visiting a new city. Incorporating sentiment analysis to identify the user’s emotions and framing the response catering to the user’s emotions can enhance the chatbot’s user experience. By integrating Long Short-Term Memory (LSTM) networks and Large Language Models (LLM), this study aims to offer the components of a comprehensive system that understands and responds to user sentiments, enhancing the tourism experience.