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Precision localization method for fake news detection across multiple domains

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Abstract

Fake news has become proliferated on the internet, resulting in significant economic losses in the real world and even destabilizing the political landscape in certain regions. Unscrupulous individuals can exploit these fabrications for illicit gains, prompting an increase in the emergence of fake news across various fields. Human detection methods are no longer sufficient for discerning the authenticity of such news, and most existing algorithms remain focused on single-domain fake news detection, which struggles to meet practical needs in terms of accuracy and timeliness. Challenges such as data distribution differences, nominal polysemy, and variations in dissemination patterns, all indicative of domain shift, cause these methods to perform poorly when applied directly. Therefore, a targeted model designed to address domain shift is necessary. In this paper, we employ multiple BERT models for word embedding and use a multi-extraction network to initially extract features, followed by domain localization module for precise domain targeting, and design a fast model to address timeliness. Our experiments demonstrate that the methods designed significantly enhance the performance of fake news detection across multiple domains. The code involved in this study is publicly available on website https://github.com/SWLee777/PLFND.

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Data availability

No datasets were generated or analyzed during the current study.

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Acknowledgements

We are deeply grateful to the researchers who shared their data and the students, teachers, and staff who helped us process data, as well as the social network users and the school for their support in our research work.

Funding

Open Project of the Research Platform of the Grain Information Processing Center of Henan University of Technology KFJJ2024009); High-level Scientific Research Foundation for the introduction of talent, Henan University of Technology (2021BS001); Postdoctoral Research Foundation, Henan University of Technology (21450028); Natural science project of Science and Technology Department of Henan Province (232102210005); High-level Talents Fund of Henan University of Technology (2022BS075); Henan Province Key R&D Project: Development and Application of Lightweight 5G Modules and Terminals for Electric Power (231111212400).

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Authors and Affiliations

  1. Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou, 450001, China

    Xuefeng Li

  2. Henan Key Laboratory of Grain Storage Information Intelligent Perception and Decision Making, Henan University of Technology, Zhengzhou, 450001, China

    Xuefeng Li

  3. School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, 450001, China

    Xuefeng Li, Jian Wei & Xiaqiong Fan

  4. Air Force Engineering University, Xi’an, 710077, China

    Chen Chen

  5. Shandong Woman’s University, Jinan, 250002, China

    Chensu Zhao

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Xuefeng Li and Chen Chen wrote the main manuscript text, Jian Wei and Chensu Zhao prepared figures and completed some experiments. Xiaqiong Fan provided some creative ideas and completed some experiments.

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Correspondence to Xuefeng Li.

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Li, X., Chen, C., Wei, J. et al. Precision localization method for fake news detection across multiple domains. J Supercomput 81, 249 (2025). https://doi.org/10.1007/s11227-024-06776-5

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