Distinguishing Arabic GenAI-generated Tweets and Human Tweets utilizing Machine Learning
Generative Artificial Intelligence (GenAI) tools, like ChatGPT, have made it easy to create text, music, images, and other types of media. GenAI, a type of AI technology, has rapidly gained fame and popularity for its ability to generate new content. Notably, its applications allow anyone to produce...
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Veröffentlicht in: | Engineering, technology & applied science research technology & applied science research, 2024-10, Vol.14 (5), p.16720-16726 |
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Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | Generative Artificial Intelligence (GenAI) tools, like ChatGPT, have made it easy to create text, music, images, and other types of media. GenAI, a type of AI technology, has rapidly gained fame and popularity for its ability to generate new content. Notably, its applications allow anyone to produce natural conversations and content, making it increasingly challenging to distinguish between human-written and GenAI-generated material. The current research focuses on Arabic content to differentiate GenAI-generated content from authentic human-written content on the X platform (Twitter). Datasets from both real human-written tweets and GenAI-generated tweets were collected. Then, three Machine Learning models were built to predict whether a tweet source is GenAI-generated or human-written. The highest achieved accuracy was 93%. |
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ISSN: | 2241-4487 1792-8036 |
DOI: | 10.48084/etasr.8249 |