NSTL国家科技图书文献中心

1. Topic-guided multi-domain fake news detection NSTL国家科技图书文献中心

Lingtao Wang | Yong Hu - 《Multimedia systems》 - 2025,31(2) - 75.1～75.15 - 共15页

摘要： dissemination of fake* news poses a significant threat to* | develop automated fake* news detection technologies* | -guided Multi-domain Fake* News Detection Framework (TG* | In the information age, news* serves as a* | , such as politics or healthcare. News* coverage spans a*

关键词： Fake news detection | Multi-domain | Social media | Deep learning

2. From news disengagement to fake news engagement: Examining the role of news-finds-me perceptions in vulnerability to fake news through third-person perception NSTL国家科技图书文献中心

Tian Y. | Willnat L. - 《Computers in human behavior》 - 2025,162(Jan.) - 1.1～1.14 - 共14页

摘要： use and vulnerability to fake* news, it remains* | contribute to fake* news susceptibility. To fill this* | examine fake* news vulnerability and engagement in* | share fake* news by creating a biased mentality that* | one is fake-news-proof while others are fake-news

关键词： Fake news | News-finds-me | Social media | Third-person perception

3. Precision localization method for fake news detection across multiple domains NSTL国家科技图书文献中心

Xuefeng Li | Chen Chen ... - 《The Journal of Supercomputing》 - 2025,81(1) - 249.1～249.20 - 共20页

摘要：Fake news has become proliferated on the | an increase in the emergence of fake* news across* | single-domain fake* news detection, which struggles to* | sufficient for discerning the authenticity of such news | designed significantly enhance the performance of fake

关键词： Fake news | Multiple domains | Domain localization

4. Cross-attention multi-perspective fusion network based fake news censorship NSTL国家科技图书文献中心

Zhang W. | Zhang M.... - 《Neurocomputing》 - 2025,611(Jan.1) - 1.1～1.10 - 共10页

摘要：© 2024 Elsevier B.V.Current fake news | -Attention Multi-Perspective Fusion Network Based Fake News | , respectively. On fake* news datasets generated by LLMs, our* | result in biases. However, news* inherently encompasses* | news environment which may offer valuable information

关键词： Cross-attention | Fake news censorship | Internal perspectives | LLMs | News environment

5. Fake News Detection Across Multiple Domains Using Fuzzy Association Rules NSTL国家科技图书文献中心

Xiaofeng Xu | Weisha Zhang ... - 《Algorithms and Architectures for Parallel Processing,Part I》 - International Conference on Algorithms and Architectures for Parallel Processing - 2025, - 1～20 - 共20页

摘要：The detection of fake* news is not confined to* | a multi-domain fake* news detection model based on* | conducted on a fake* news dataset demonstrate that our* | detection in fake* news identification and improves the* | fake news detection.

关键词： Fake news detection | Social media | Multi-domain | Fuzzy rules

6. Modelling Context and Content Features for Fake News Detection NSTL国家科技图书文献中心

Huyen Trang Phan | Dosam Hwang ... - 《Expert systems》 - 2025,42(3) - e13839～1 - 共11页

摘要： dissemination of fake news and preventing the spread of fake | have been proposed to detect fake* news, but they do* | context and content in fake* news detection. This study* | proposes a method to improve the performance of fake news | social networks, an increasing amount of news* has been*

关键词： fake news detection | GCN | modelling content features | modelling context features

7. Fake news detection based on multi-modal domain adaptation NSTL国家科技图书文献中心

Xiaopei,Wang | Jiana,Meng ... - 《Neural computing & applications》 - 2025,37(7) - 5781～5793 - 共13页

摘要： role of fake* news detection in cybersecurity* | -modal fake* news detection model based on the multi* | effectiveness of the fake* news detection task.* | to the unguaranteed authenticity of news, and the | as the text and images of news, and propose a multi

关键词： Multi-modal | Fake news detection | EfficientNet | Domain adaptation

8. Topic-Awared Contrastive Learning for Incoming Fake News Detection in News Streams NSTL国家科技图书文献中心

Yongcheng Zhang | Changpeng Xiang ... - 《Natural Language Processing and Chinese Computing,Part V》 - CCF International Conference on Natural Language Processing and Chinese Computing - 2025, - 43～54 - 共12页

摘要： spread of fake* news poses a significant challenge to* | . Traditional fake* news detection methods, which focus on* | their ability to effectively detect fake news | detects fake* news in news streams, outperforming* | analyzing individual articles in news* streams, often*

关键词： Fake news detection | Incremental clustering | Contrastive learning

9. Knowledge-aware multimodal pre-training for fake news detection NSTL国家科技图书文献中心

Zhang, Litian | Zhang, Xiaoming ... - 《Information Fusion》 - 2025,114 - 共11页

摘要： fake news across various social media platforms, the | characteristic of fake* news lies in its diversity, encompassing* | fake news, leading to limited universality. Moreover | of fake news. To address these challenges, we | paradigm for fake* news detection, dubbed KAMP. Our*

关键词： Multimodal fake news detection | Knowledge-aware | Pre-training

10. Potential Features Fusion Network for Multimodal Fake News Detection NSTL国家科技图书文献中心

FEIFEI KOU | BINGWEI WANG ... - 《ACM transactions on multimedia computing communications and applications》 - 2025,21(3) - 87.1～87.24 - 共24页

摘要：, fake* news is also widely and rapidly spreading, which* | to detect fake* news automatically and efficiently* | and fake* news detection. Besides, we also extract* | process the news* image separately, which can best use* | the relationships between the news* image category*

摘要： dissemination of fake* news poses a significant threat to* | develop automated fake* news detection technologies* | -guided Multi-domain Fake* News Detection Framework (TG* | In the information age, news* serves as a* | , such as politics or healthcare. News* coverage spans a*

关键词： Fake news detection | Multi-domain | Social media | Deep learning

摘要： use and vulnerability to fake* news, it remains* | contribute to fake* news susceptibility. To fill this* | examine fake* news vulnerability and engagement in* | share fake* news by creating a biased mentality that* | one is fake-news-proof while others are fake-news

关键词： Fake news | News-finds-me | Social media | Third-person perception

摘要：Fake news has become proliferated on the | an increase in the emergence of fake* news across* | single-domain fake* news detection, which struggles to* | sufficient for discerning the authenticity of such news | designed significantly enhance the performance of fake

关键词： Fake news | Multiple domains | Domain localization

摘要：© 2024 Elsevier B.V.Current fake news | -Attention Multi-Perspective Fusion Network Based Fake News | , respectively. On fake* news datasets generated by LLMs, our* | result in biases. However, news* inherently encompasses* | news environment which may offer valuable information

关键词： Cross-attention | Fake news censorship | Internal perspectives | LLMs | News environment

摘要：The detection of fake* news is not confined to* | a multi-domain fake* news detection model based on* | conducted on a fake* news dataset demonstrate that our* | detection in fake* news identification and improves the* | fake news detection.

关键词： Fake news detection | Social media | Multi-domain | Fuzzy rules

关键词： fake news detection | GCN | modelling content features | modelling context features

摘要： role of fake* news detection in cybersecurity* | -modal fake* news detection model based on the multi* | effectiveness of the fake* news detection task.* | to the unguaranteed authenticity of news, and the | as the text and images of news, and propose a multi

关键词： Multi-modal | Fake news detection | EfficientNet | Domain adaptation

摘要： spread of fake* news poses a significant challenge to* | . Traditional fake* news detection methods, which focus on* | their ability to effectively detect fake news | detects fake* news in news streams, outperforming* | analyzing individual articles in news* streams, often*

关键词： Fake news detection | Incremental clustering | Contrastive learning

摘要： fake news across various social media platforms, the | characteristic of fake* news lies in its diversity, encompassing* | fake news, leading to limited universality. Moreover | of fake news. To address these challenges, we | paradigm for fake* news detection, dubbed KAMP. Our*

关键词： Multimodal fake news detection | Knowledge-aware | Pre-training

摘要：, fake* news is also widely and rapidly spreading, which* | to detect fake* news automatically and efficiently* | and fake* news detection. Besides, we also extract* | process the news* image separately, which can best use* | the relationships between the news* image category*

关键词： Fake news detection | multi-modal fusing | neural network | social media

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： dissemination of fake news poses a significant threat to | develop automated fake news detection technologies | -guided Multi-domain Fake News Detection Framework (TG | In the information age, news serves as a | , such as politics or healthcare. News coverage spans a

关键词： Fake news detection | Multi-domain | Social media | Deep learning

摘要： use and vulnerability to fake news, it remains | contribute to fake news susceptibility. To fill this | examine fake news vulnerability and engagement in | share fake news by creating a biased mentality that | one is fake-news-proof while others are fake-news

关键词： Fake news | News-finds-me | Social media | Third-person perception

摘要：Fake news has become proliferated on the | an increase in the emergence of fake news across | single-domain fake news detection, which struggles to | sufficient for discerning the authenticity of such news | designed significantly enhance the performance of fake

关键词： Fake news | Multiple domains | Domain localization

摘要：© 2024 Elsevier B.V.Current fake news | -Attention Multi-Perspective Fusion Network Based Fake News | , respectively. On fake news datasets generated by LLMs, our | result in biases. However, news inherently encompasses | news environment which may offer valuable information

关键词： Cross-attention | Fake news censorship | Internal perspectives | LLMs | News environment

摘要：The detection of fake news is not confined to | a multi-domain fake news detection model based on | conducted on a fake news dataset demonstrate that our | detection in fake news identification and improves the | fake news detection.

关键词： Fake news detection | Social media | Multi-domain | Fuzzy rules

摘要： dissemination of fake news and preventing the spread of fake | have been proposed to detect fake news, but they do | context and content in fake news detection. This study | proposes a method to improve the performance of fake news | social networks, an increasing amount of news has been

关键词： fake news detection | GCN | modelling content features | modelling context features

摘要： role of fake news detection in cybersecurity | -modal fake news detection model based on the multi | effectiveness of the fake news detection task. | to the unguaranteed authenticity of news, and the | as the text and images of news, and propose a multi

关键词： Multi-modal | Fake news detection | EfficientNet | Domain adaptation

摘要： spread of fake news poses a significant challenge to | . Traditional fake news detection methods, which focus on | their ability to effectively detect fake news | detects fake news in news streams, outperforming | analyzing individual articles in news streams, often

关键词： Fake news detection | Incremental clustering | Contrastive learning

摘要： fake news across various social media platforms, the | characteristic of fake news lies in its diversity, encompassing | fake news, leading to limited universality. Moreover | of fake news. To address these challenges, we | paradigm for fake news detection, dubbed KAMP. Our

关键词： Multimodal fake news detection | Knowledge-aware | Pre-training

摘要：, fake news is also widely and rapidly spreading, which | to detect fake news automatically and efficiently | and fake news detection. Besides, we also extract | process the news image separately, which can best use | the relationships between the news image category

关键词： Fake news detection | multi-modal fusing | neural network | social media

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： dissemination of fake* news poses a significant threat to* | develop automated fake* news detection technologies* | -guided Multi-domain Fake* News Detection Framework (TG* | In the information age, news* serves as a* | , such as politics or healthcare. News* coverage spans a*

摘要： use and vulnerability to fake* news, it remains* | contribute to fake* news susceptibility. To fill this* | examine fake* news vulnerability and engagement in* | share fake* news by creating a biased mentality that* | one is fake-news-proof while others are fake-news

摘要：Fake news has become proliferated on the | an increase in the emergence of fake* news across* | single-domain fake* news detection, which struggles to* | sufficient for discerning the authenticity of such news | designed significantly enhance the performance of fake

摘要：© 2024 Elsevier B.V.Current fake news | -Attention Multi-Perspective Fusion Network Based Fake News | , respectively. On fake* news datasets generated by LLMs, our* | result in biases. However, news* inherently encompasses* | news environment which may offer valuable information

摘要：The detection of fake* news is not confined to* | a multi-domain fake* news detection model based on* | conducted on a fake* news dataset demonstrate that our* | detection in fake* news identification and improves the* | fake news detection.

摘要： role of fake* news detection in cybersecurity* | -modal fake* news detection model based on the multi* | effectiveness of the fake* news detection task.* | to the unguaranteed authenticity of news, and the | as the text and images of news, and propose a multi

摘要： spread of fake* news poses a significant challenge to* | . Traditional fake* news detection methods, which focus on* | their ability to effectively detect fake news | detects fake* news in news streams, outperforming* | analyzing individual articles in news* streams, often*

摘要： fake news across various social media platforms, the | characteristic of fake* news lies in its diversity, encompassing* | fake news, leading to limited universality. Moreover | of fake news. To address these challenges, we | paradigm for fake* news detection, dubbed KAMP. Our*

摘要：, fake* news is also widely and rapidly spreading, which* | to detect fake* news automatically and efficiently* | and fake* news detection. Besides, we also extract* | process the news* image separately, which can best use* | the relationships between the news* image category*