Modality deep-learning frameworks for fake news detection on social networks: a systematic literature review
Fake news on social networks is a challenging problem due to the rapid dissemination and
volume of information, as well as the ease of creating and sharing content anonymously …
volume of information, as well as the ease of creating and sharing content anonymously …
A systematic literature review and meta-analysis of studies on online fake news detection
The ubiquitous access and exponential growth of information available on social media
networks have facilitated the spread of fake news, complicating the task of distinguishing …
networks have facilitated the spread of fake news, complicating the task of distinguishing …
Factify 2: A multimodal fake news and satire news dataset
The internet gives the world an open platform to express their views and share their stories.
While this is very valuable, it makes fake news one of our society's most pressing problems …
While this is very valuable, it makes fake news one of our society's most pressing problems …
ContCommRTD: A distributed content-based misinformation-aware community detection system for real-time disaster reporting
Real-time social media data can provide useful information on evolving hazards. Alongside
traditional methods of disaster detection, the integration of social media data can …
traditional methods of disaster detection, the integration of social media data can …
Multilingual deep learning framework for fake news detection using capsule neural network
Fake news detection is an essential task; however, the complexity of several languages
makes fake news detection challenging. It requires drawing many conclusions about the …
makes fake news detection challenging. It requires drawing many conclusions about the …
GBERT: A hybrid deep learning model based on GPT-BERT for fake news detection
The digital era has expanded social exposure with easy internet access for mobile users,
allowing for global communication. Now, people can get to know what is going on around …
allowing for global communication. Now, people can get to know what is going on around …
Computers' interpretations of knowledge representation using pre-conceptual schemas: An approach based on the bert and llama 2-chat models
J Insuasti, F Roa, CM Zapata-Jaramillo - Big Data and Cognitive …, 2023 - mdpi.com
Pre-conceptual schemas are a straightforward way to represent knowledge using controlled
language regardless of context. Despite the benefits of using pre-conceptual schemas by …
language regardless of context. Despite the benefits of using pre-conceptual schemas by …
[HTML][HTML] Exploiting stance similarity and graph neural networks for fake news detection
K Soga, S Yoshida, M Muneyasu - Pattern Recognition Letters, 2024 - Elsevier
The widespread dissemination of fake news on social media has substantial economic and
social implications. Although traditional propagation-based methods employing graph …
social implications. Although traditional propagation-based methods employing graph …
[HTML][HTML] Navigating the Multimodal Landscape: A Review on Integration of Text and Image Data in Machine Learning Architectures
Images and text have become essential parts of the multimodal machine learning (MMML)
framework in today's world because data are always available, and technological …
framework in today's world because data are always available, and technological …
Roberta-gcn: A novel approach for combating fake news in bangla using advanced language processing and graph convolutional networks
In this era of widespread information, combating fake news in less commonly represented
languages like Bengali is a significant challenge. Fake news is a critical issue in Bangla, a …
languages like Bengali is a significant challenge. Fake news is a critical issue in Bangla, a …