Combating misinformation in the age of llms: Opportunities and challenges
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 …
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
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 …
absence of a comprehensive review on it, this research aims to conduct a comprehensive …
A survey on automated fact-checking
Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …
information and misinformation can spread in the modern media ecosystem. Therefore …
[HTML][HTML] Fake news detection: A hybrid CNN-RNN based deep learning approach
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 …
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
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 …
information, which leads to rumors being circulated. Meanwhile, detecting rumors from such …
Fang: Leveraging social context for fake news detection using graph representation
We propose Factual News Graph (FANG), a novel graphical social context representation
and learning framework for fake news detection. Unlike previous contextual models that …
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 …
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 …
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 …
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 …
contents, and can be spread quickly with social media. People can be easily deceived by …