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Article History

Received: 14 July 2023

Accepted: 1 April 2025

First Online: 20 May 2025

Declarations

:

: The authors have no conflict of interest to declare.

: The implementation code of our model will be open-sourced under the MIT license on GitHub upon publication of the paper. The open-source repository will include scripts for data preprocessing, model training, evaluation, and all dependencies required to replicate the results presented in the paper. The purpose of open-sourcing is to enhance the transparency of the research and to facilitate further studies and applications in the academic community.

: When collecting and processing news data, it is important to ensure the protection of personal information. Additionally, the boundaries of data usage should be clearly defined to avoid unauthorized surveillance or other infringements on personal privacy. To prevent technological misuse, it is recommended to establish strict usage guidelines and ethical frameworks. When deploying such technologies, transparency processes should be implemented to ensure their use for legitimate purposes, and potential negative impacts should be monitored and evaluated. Through these measures, we aim to ensure that research on long-text fake news detection technology is not only scientifically effective, but also adheres to ethical standards, contributing to the creation of a more transparent and trustworthy societal environment for information.