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
|Title of host publication
|2023 International Conference on Big Data, Knowledge and Control Systems Engineering (BdKCSE)
|Subtitle of host publication
|Big Data, Knowledge and Control Systems Engineering
|Lyubka Doukovska, Svetozar Ilchev, Edita Djambuova, Valentina Terzieva, Rumen Andreev
|Number of pages
|E-pub ahead of print - 11 Dec 2023
|2023 International Conference on Big Data, Knowledge and Control Systems Engineering - Sofia, Bulgaria
Duration: 2 Nov 2023 → 3 Nov 2023
|Proceedings of the 8th International Conference on Big Data, Knowledge and Control Systems Engineering, BdKCSE 2023
|2023 International Conference on Big Data, Knowledge and Control Systems Engineering
|2/11/23 → 3/11/23
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- Generative Artificial Intelligence chatbots
- higher education
- topic modelling
- sentiment analysis