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Majhi, Debasis
- Scholarly Communication and Machine-Generated Text: Is it Finally AI vs AI in Plagiarism Detection?
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Authors
Affiliations
1 Assistant Librarian, DSMS College, Durgapur - 713206, Durgapur, West Bengal, IN
2 Research Scholar, Banaras Hindu University, Varanasi – 221002, Uttar Pradesh, IN
1 Assistant Librarian, DSMS College, Durgapur - 713206, Durgapur, West Bengal, IN
2 Research Scholar, Banaras Hindu University, Varanasi – 221002, Uttar Pradesh, IN
Source
Journal of Information and Knowledge (Formerly SRELS Journal of Information Management), Vol 60, No 3 (2023), Pagination: 173-181Abstract
This study utilizes GPT (Generative Pre-Trained Transformer) language model-based AI writing tools to create a set of 80 academic writing samples based on the eight themes of the experiential sessions of the LTC 2023. These samples, each between 2000 and 2500 words long, are then analyzed using both conventional plagiarism detection tools and selected AI detection tools. The study finds that traditional syntactic similarity-based anti-plagiarism tools struggle to detect AI-generated text due to the differences in syntax and structure between machine-generated and human-written text. However, the researchers discovered that AI detector tools can be used to catch AI-generated content based on specific characteristics that are typical of machine-generated text. The paper concludes by posing the question of whether we are entering an era in which AI detectors will be used to prevent AI-generated content from entering the scholarly communication process. This research sheds light on the challenges associated with AI-generated content in the academic research literature and offers a potential solution for detecting and preventing plagiarism in this context.Keywords
AI (Artificial Intelligence), GPT (Generative Pre-Training Transformer), Machine Learning, ChatGPT, Natural Language Processing (NLP), OpenAI, Plagiarism.
References
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- Sleeping Beauties in Four Epic Works on Library Science by S. R. Ranganathan: An Analytical Study
Abstract Views :18 |
PDF Views:3
Authors
Affiliations
1 Library Assistant, Ramakrishna Mission Vivekananda Educational and Research Institute (RKMVU), Ranchi – 834008, Jharkhand, IN
2 Assistant Librarian, DSMS College, Durgapur – 713206, Durgapur, West Bengal, IN
3 Research Scholar, Banaras Hindu University, Varanasi – 221005, Uttar Pradesh, IN
1 Library Assistant, Ramakrishna Mission Vivekananda Educational and Research Institute (RKMVU), Ranchi – 834008, Jharkhand, IN
2 Assistant Librarian, DSMS College, Durgapur – 713206, Durgapur, West Bengal, IN
3 Research Scholar, Banaras Hindu University, Varanasi – 221005, Uttar Pradesh, IN
Source
Journal of Information and Knowledge (Formerly SRELS Journal of Information Management), Vol 60, No 4 (2023), Pagination: 253-260Abstract
Dr. S. R. Ranganathan, an Indian librarian and educator who is known as the 'Father of Library Science in India', is also widely known throughout the rest of the world due to his worldwide contribution to library science. Earlier it was difficult to find citations to prominent old research works. New computer technology helps find these types of articles more easily and it also finds sleeping beauties in several disciplines. Here the term 'Sleeping beauty' is used to define a research article life (year) that has been relatively uncited for several years and then suddenly attracts a lot of attention. The present paper describes four sleeping beauties that are found from Ranganathan’s contributions (books only) in library science, such as; Colon Classification (1933), Prolegomena to Library Classification (1937), Philosophy of Library Classification (1951) and Reference Service (1961). Above mentioned four sleeping beauties are detected using three main criteria; depth of sleep, length of sleep, and awakening intensity given by Van Raan (2015) to detect the sleeping beauties.Keywords
Sleeping Beauties, Library and Information Science, Premature Discovery, Ranganathan S. R., Resisted Discovery.References
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