A survey of multi-modal knowledge graphs: Technologies and trends
In recent years, Knowledge Graphs (KGs) have played a crucial role in the development of
advanced knowledge-intensive applications, such as recommender systems and semantic …
advanced knowledge-intensive applications, such as recommender systems and semantic …
[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 …
Compare to the knowledge: Graph neural fake news detection with external knowledge
Nowadays, fake news detection, which aims to verify whether a news document is trusted or
fake, has become urgent and important. Most existing methods rely heavily on linguistic and …
fake, has become urgent and important. Most existing methods rely heavily on linguistic and …
[PDF][PDF] Multimodal fusion with co-attention networks for fake news detection
Y Wu, P Zhan, Y Zhang, L Wang… - Findings of the association …, 2021 - aclanthology.org
Fake news with textual and visual contents has a better story-telling ability than text-only
contents, and can be spread quickly with social media. People can be easily deceived by …
contents, and can be spread quickly with social media. People can be easily deceived by …
Twibot-22: Towards graph-based twitter bot detection
Twitter bot detection has become an increasingly important task to combat misinformation,
facilitate social media moderation, and preserve the integrity of the online discourse. State-of …
facilitate social media moderation, and preserve the integrity of the online discourse. State-of …
Hierarchical multi-modal contextual attention network for fake news detection
Nowadays, detecting fake news on social media platforms has become a top priority since
the widespread dissemination of fake news may mislead readers and have negative effects …
the widespread dissemination of fake news may mislead readers and have negative effects …
Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions
Fake news and disinformation (FNaD) are increasingly being circulated through various
online and social networking platforms, causing widespread disruptions and influencing …
online and social networking platforms, causing widespread disruptions and influencing …
Ddgcn: Dual dynamic graph convolutional networks for rumor detection on social media
Detecting rumors on social media has become particular important due to the rapid
dissemination and adverse impacts on our lives. Though a set of rumor detection models …
dissemination and adverse impacts on our lives. Though a set of rumor detection models …
Multimodal sentiment detection based on multi-channel graph neural networks
With the popularity of smartphones, we have witnessed the rapid proliferation of multimodal
posts on various social media platforms. We observe that the multimodal sentiment …
posts on various social media platforms. We observe that the multimodal sentiment …
Improving fake news detection with domain-adversarial and graph-attention neural network
H Yuan, J Zheng, Q Ye, Y Qian, Y Zhang - Decision Support Systems, 2021 - Elsevier
With the widespread use of online social media, we have witnessed that fake news causes
enormous distress and inconvenience to people's social life. Although previous studies have …
enormous distress and inconvenience to people's social life. Although previous studies have …