A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts
This paper presents a pioneering and comprehensive analysis of fake text, a pressing issue in the digital age, by categorizing it into two main types: Misinformation and LM-generated texts. It is the first study to systematically dissect and examine the intricate challenges and nuances in distinguis...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10870239/ |
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| _version_ | 1823857120357908480 |
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| author | Soonchan Kwon Beakcheol Jang |
| author_facet | Soonchan Kwon Beakcheol Jang |
| author_sort | Soonchan Kwon |
| collection | DOAJ |
| description | This paper presents a pioneering and comprehensive analysis of fake text, a pressing issue in the digital age, by categorizing it into two main types: Misinformation and LM-generated texts. It is the first study to systematically dissect and examine the intricate challenges and nuances in distinguishing between genuine and artificial text. Through a meticulous review of various methodologies and technologies in fake text detection, the paper provides an in-depth evaluation of their effectiveness across diverse scenarios. Furthermore, this research delves into the significant societal impacts of both misinformation and LM-generated texts, underlining the urgent need for precise and effective detection mechanisms in our increasingly information-saturated world. This extensive survey not only offers a unique perspective on the current landscape of fake text detection, but also paves the way for future research, highlighting critical areas where further innovation and exploration are essential. |
| format | Article |
| id | doaj-art-342f3de23e20445084d80f8d9131c51f |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-342f3de23e20445084d80f8d9131c51f2025-02-12T00:02:09ZengIEEEIEEE Access2169-35362025-01-0113253012532410.1109/ACCESS.2025.353880510870239A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated TextsSoonchan Kwon0https://orcid.org/0009-0007-8600-7092Beakcheol Jang1https://orcid.org/0000-0002-3911-5935Graduate School of Information, Yonsei University, Seoul, South KoreaGraduate School of Information, Yonsei University, Seoul, South KoreaThis paper presents a pioneering and comprehensive analysis of fake text, a pressing issue in the digital age, by categorizing it into two main types: Misinformation and LM-generated texts. It is the first study to systematically dissect and examine the intricate challenges and nuances in distinguishing between genuine and artificial text. Through a meticulous review of various methodologies and technologies in fake text detection, the paper provides an in-depth evaluation of their effectiveness across diverse scenarios. Furthermore, this research delves into the significant societal impacts of both misinformation and LM-generated texts, underlining the urgent need for precise and effective detection mechanisms in our increasingly information-saturated world. This extensive survey not only offers a unique perspective on the current landscape of fake text detection, but also paves the way for future research, highlighting critical areas where further innovation and exploration are essential.https://ieeexplore.ieee.org/document/10870239/Nature language processinglarge language modelfake text detectiondeep learning |
| spellingShingle | Soonchan Kwon Beakcheol Jang A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts IEEE Access Nature language processing large language model fake text detection deep learning |
| title | A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts |
| title_full | A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts |
| title_fullStr | A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts |
| title_full_unstemmed | A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts |
| title_short | A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts |
| title_sort | comprehensive survey of fake text detection on misinformation and lm generated texts |
| topic | Nature language processing large language model fake text detection deep learning |
| url | https://ieeexplore.ieee.org/document/10870239/ |
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