Cargando…
Self Multi-Head Attention-based Convolutional Neural Networks for fake news detection
With the rapid development of the internet, social media has become an essential tool for getting information, and attracted a large number of people join the social media platforms because of its low cost, accessibility and amazing content. It greatly enriches our life. However, its rapid developme...
Autores principales: | Fang, Yong, Gao, Jian, Huang, Cheng, Peng, Hua, Wu, Runpu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6762082/ https://www.ncbi.nlm.nih.gov/pubmed/31557213 http://dx.doi.org/10.1371/journal.pone.0222713 |
Ejemplares similares
-
DC-CNN: Dual-channel Convolutional Neural Networks with attention-pooling for fake news detection
por: Ma, Kun, et al.
Publicado: (2022) -
Mul-FaD: attention based detection of multiLingual fake news
por: Ahuja, Nishtha, et al.
Publicado: (2023) -
Sentiment Analysis for Fake News Detection by Means of Neural Networks
por: Kula, Sebastian, et al.
Publicado: (2020) -
“Fake Tan” or “Fake News”?
por: Meyer, Georg, et al.
Publicado: (2020) -
EchoFakeD: improving fake news detection in social media with an efficient deep neural network
por: Kaliyar, Rohit Kumar, et al.
Publicado: (2021)