Combating misinformation in the age of llms: Opportunities and challenges

C Chen, K Shu - AI Magazine, 2024 - Wiley Online Library
Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

[HTML][HTML] Application and theory gaps during the rise of artificial intelligence in education

X Chen, H Xie, D Zou, GJ Hwang - Computers and Education: Artificial …, 2020 - Elsevier
Considering the increasing importance of Artificial Intelligence in Education (AIEd) and the
absence of a comprehensive review on it, this research aims to conduct a comprehensive …

A survey on automated fact-checking

Z Guo, M Schlichtkrull, A Vlachos - Transactions of the Association for …, 2022 - direct.mit.edu
Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …

[HTML][HTML] Fake news detection: A hybrid CNN-RNN based deep learning approach

JA Nasir, OS Khan, I Varlamis - International Journal of Information …, 2021 - Elsevier
The explosion of social media allowed individuals to spread information without cost, with
little investigation and fewer filters than before. This amplified the old problem of fake news …

Rumor detection on social media with bi-directional graph convolutional networks

T Bian, X Xiao, T Xu, P Zhao, W Huang… - Proceedings of the …, 2020 - ojs.aaai.org
Social media has been developing rapidly in public due to its nature of spreading new
information, which leads to rumors being circulated. Meanwhile, detecting rumors from such …

Fang: Leveraging social context for fake news detection using graph representation

VH Nguyen, K Sugiyama, P Nakov… - Proceedings of the 29th …, 2020 - dl.acm.org
We propose Factual News Graph (FANG), a novel graphical social context representation
and learning framework for fake news detection. Unlike previous contextual models that …

GCAN: Graph-aware co-attention networks for explainable fake news detection on social media

YJ Lu, CT Li - arXiv preprint arXiv:2004.11648, 2020 - arxiv.org
This paper solves the fake news detection problem under a more realistic scenario on social
media. Given the source short-text tweet and the corresponding sequence of retweet users …

An overview of online fake news: Characterization, detection, and discussion

X Zhang, AA Ghorbani - Information Processing & Management, 2020 - Elsevier
Over the recent years, the growth of online social media has greatly facilitated the way
people communicate with each other. Users of online social media share information …

Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges and opportunities

P Meel, DK Vishwakarma - Expert Systems with Applications, 2020 - Elsevier
Internet and social media have become a widespread, large scale and easy to use platform
for real-time information dissemination. It has become an open stage for discussion …

[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 …