Exploring Public Opinions Toward the Use of Generative Artificial Intelligence Chatbot in Higher Education: An Insight from Topic Modelling and Sentiment Analysis

The Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education, so this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the tweets. User sentiments were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

I. Introduction

Generative Artificial Intelligence (GAI) chatbots are advanced chatbot systems that use generative models to respond to user inputs in a human-like manner. GAI chatbots have the potential to generate interactive dialogues by establishing chatbots that simulate conversations with native speakers. They use different techniques to generate text-either generative pre-trained transformer (GPT) chatbot or large language models (LLMs).