Ethical Considerations for Artificial Intelligence Tools in Academic Research and Manuscript Preparation: A Web Content Analysis
Digital Transformation in Higher Education, Part B
ISBN: 978-1-83608-425-9, eISBN: 978-1-83608-424-2
Publication date: 28 October 2024
Abstract
Our research investigated the potential effects of incorporating artificial intelligence (AI) techniques into scholarly publications, specifically big language models. The study employs a qualitative methodology and web content analysis to understand various publishers' guidelines. It examines the potential applications and outcomes of AI in publishers. The analysis has revealed insightful findings regarding the use and implications of AI tools in academic publishing. Agglomeration analysis has uncovered distinct clusters of terms, indicating semantic relationships and thematic cohesion within the dataset. Notably, ‘Large’ and ‘Models’ have formed a coherent cluster, highlighting the significance of large-scale language models in scholarly discourse. Similarly, factor analysis has identified thematic clusters related to AI usage, emphasising aspects such as accuracy, responsibility and the role of authors in AI-assisted work. Semantic mapping has further elucidated thematic dimensions, highlighting linguistic frameworks, work-related constructs, methodological frameworks, AI technologies and publication dynamics. Evaluation metrics have consistently demonstrated cohesion, coherence and lexical diversity across varying numbers of topics, underscoring the robustness of the semantic mapping approach. Additionally, the Silhouette coefficient has provided insights into cluster quality, indicating strong cohesion within specific thematic clusters while hinting at potential overlaps in others. Co-occurrence matrix and cross-tabulation analysis have revealed association and frequency distribution patterns among terms, shedding light on prevalent themes and topics within the dataset. Finally, the proximity plot has illustrated the strength of associations between keywords and accuracy, emphasising central themes and moderate thematic relevance.
Keywords
Acknowledgements
Acknowledgements
We would like to express our sincere appreciation to Grammarly and ChatGPT 3.5 for providing us with an invaluable tool that significantly enhanced the quality of our work. Grammarly's comprehensive grammar checking, clarity suggestions and writing enhancement features played a crucial role in refining the language and structure of our manuscript. We would also like to sincerely thank Provalis Research for providing us with access to WordStat 2023, an invaluable software tool that greatly facilitated our research endeavours. WordStat 2023's powerful text mining and analysis capabilities were vital in extracting meaningful insights from large volumes of textual data, enabling us to uncover patterns, trends and relationships relevant to our research objectives. We are truly grateful to the team at Provalis Research for their dedication to developing innovative solutions for text analysis and their commitment to supporting academic and research initiatives.
Citation
Aslam, M.S. and Nisar, S. (2024), "Ethical Considerations for Artificial Intelligence Tools in Academic Research and Manuscript Preparation: A Web Content Analysis", Lytras, M.D., Serban, A.C., Alkhaldi, A., Malik, S. and Aldosemani, T. (Ed.) Digital Transformation in Higher Education, Part B (Emerald Studies in Active and Transformative Learning in Higher Education), Emerald Publishing Limited, Leeds, pp. 155-196. https://doi.org/10.1108/978-1-83608-424-220241007
Publisher
:Emerald Publishing Limited
Copyright © 2024 Muhammad Shahzad Aslam and Saima Nisar. Published under exclusive licence by Emerald Publishing Limited