[HTML][HTML] Deep learning for fake news detection: A comprehensive survey
The information age enables people to obtain news online through various channels, yet in
the meanwhile making false news spread at unprecedented speed. Fake news exerts …
the meanwhile making false news spread at unprecedented speed. Fake news exerts …
End-to-end transformer-based models in textual-based NLP
A Rahali, MA Akhloufi - AI, 2023 - mdpi.com
Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …
Transformer-based models for combating rumours on microblogging platforms: a review
The remarkable success of Transformer-based embeddings in natural language tasks has
sparked interest among researchers in applying them to classify rumours on social media …
sparked interest among researchers in applying them to classify rumours on social media …
Novel approaches for fake news detection based on attention-based deep multiple-instance learning using contextualized neural language models
KM Karaoğlan - Neurocomputing, 2024 - Elsevier
With the rapid growth of social media and online news sources, the spread of fake news
(FN) has become a significant concern. Classifying FN requires sophisticated approaches to …
(FN) has become a significant concern. Classifying FN requires sophisticated approaches to …
Utilizing ensemble learning for detecting multi-modal fake news
The spread of fake news has become a critical problem in recent years due extensive use of
social media platforms. False stories can go viral quickly, reaching millions of people before …
social media platforms. False stories can go viral quickly, reaching millions of people before …
Multimodal misinformation detection by learning from synthetic data with multimodal LLMs
F Zeng, W Li, W Gao, Y Pang - arXiv preprint arXiv:2409.19656, 2024 - arxiv.org
Detecting multimodal misinformation, especially in the form of image-text pairs, is crucial.
Obtaining large-scale, high-quality real-world fact-checking datasets for training detectors is …
Obtaining large-scale, high-quality real-world fact-checking datasets for training detectors is …
Enhancing Social Media User's Trust: A Comprehensive Framework for Detecting Malicious Profiles Using Multi-Dimensional Analytics
S Terumalasetti, SR Reeja - IEEE Access, 2024 - ieeexplore.ieee.org
Information transparency, user privacy, and digital security are significantly vulnerable to the
proliferation of counterfeit bot accounts on OSN. Traditional methods for distinguishing these …
proliferation of counterfeit bot accounts on OSN. Traditional methods for distinguishing these …
FNDEX: Fake News and Doxxing Detection with Explainable AI
D Sallami, E Aïmeur - arXiv preprint arXiv:2410.22390, 2024 - arxiv.org
The widespread and diverse online media platforms and other internet-driven
communication technologies have presented significant challenges in defining the …
communication technologies have presented significant challenges in defining the …
GraMuFeN: graph-based multi-modal fake news detection in social media
Nowadays media overload is a pretty common scenario all around the world. The
prevalence of media overload grants both individuals and governmental entities the ability to …
prevalence of media overload grants both individuals and governmental entities the ability to …
Joint Decision Network with Modality-Specific and Dual Interactive Features for Fake News Detection
Fake news detection has achieved considerable progress in recent years, especially since
multi-modal information was considered. However, most methods concentrate on feature …
multi-modal information was considered. However, most methods concentrate on feature …