Deepfake tweets automatic detection
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866910499759718400 |
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| author | Frej, Adam Kaminski, Adrian Marciniak, Piotr Szmajdzinski, Szymon Kuntur, Soveatin Wroblewska, Anna |
| author_facet | Frej, Adam Kaminski, Adrian Marciniak, Piotr Szmajdzinski, Szymon Kuntur, Soveatin Wroblewska, Anna |
| contents | This study addresses the critical challenge of detecting DeepFake tweets by leveraging advanced natural language processing (NLP) techniques to distinguish between genuine and AI-generated texts. Given the increasing prevalence of misinformation, our research utilizes the TweepFake dataset to train and evaluate various machine learning models. The objective is to identify effective strategies for recognizing DeepFake content, thereby enhancing the integrity of digital communications. By developing reliable methods for detecting AI-generated misinformation, this work contributes to a more trustworthy online information environment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_16489 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Deepfake tweets automatic detection Frej, Adam Kaminski, Adrian Marciniak, Piotr Szmajdzinski, Szymon Kuntur, Soveatin Wroblewska, Anna Computation and Language This study addresses the critical challenge of detecting DeepFake tweets by leveraging advanced natural language processing (NLP) techniques to distinguish between genuine and AI-generated texts. Given the increasing prevalence of misinformation, our research utilizes the TweepFake dataset to train and evaluate various machine learning models. The objective is to identify effective strategies for recognizing DeepFake content, thereby enhancing the integrity of digital communications. By developing reliable methods for detecting AI-generated misinformation, this work contributes to a more trustworthy online information environment. |
| title | Deepfake tweets automatic detection |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2406.16489 |