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 …
Stance detection on social media: State of the art and trends
Stance detection on social media is an emerging opinion mining paradigm for various social
and political applications in which sentiment analysis may be sub-optimal. There has been a …
and political applications in which sentiment analysis may be sub-optimal. There has been a …
MDFEND: Multi-domain fake news detection
Fake news spread widely on social media in various domains, which lead to real-world
threats in many aspects like politics, disasters, and finance. Most existing approaches focus …
threats in many aspects like politics, disasters, and finance. Most existing approaches focus …
Interpretable rumor detection in microblogs by attending to user interactions
We address rumor detection by learning to differentiate between the community's response
to real and fake claims in microblogs. Existing state-of-the-art models are based on tree …
to real and fake claims in microblogs. Existing state-of-the-art models are based on tree …
Rumor detection on social media with graph adversarial contrastive learning
Rumors spread through the Internet, especially on Twitter, have harmed social stability and
residents' daily lives. Recently, in addition to utilizing the text features of posts for rumor …
residents' daily lives. Recently, in addition to utilizing the text features of posts for rumor …
A survey on stance detection for mis-and disinformation identification
Understanding attitudes expressed in texts, also known as stance detection, plays an
important role in systems for detecting false information online, be it misinformation …
important role in systems for detecting false information online, be it misinformation …
[HTML][HTML] CB-Fake: A multimodal deep learning framework for automatic fake news detection using capsule neural network and BERT
The progressive growth of today's digital world has made news spread exponentially faster
on social media platforms like Twitter, Facebook, and Weibo. Unverified news is often …
on social media platforms like Twitter, Facebook, and Weibo. Unverified news is often …
Fuzzy detection system for rumors through explainable adaptive learning
Nowadays, rumor spreading has gradually evolved into a kind of organized behaviors,
accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection …
accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection …
Divide-and-conquer: Post-user interaction network for fake news detection on social media
Fake News detection has attracted much attention in recent years. Social context based
detection methods attempt to model the spreading patterns of fake news by utilizing the …
detection methods attempt to model the spreading patterns of fake news by utilizing the …
The future of false information detection on social media: New perspectives and trends
The massive spread of false information on social media has become a global risk, implicitly
influencing public opinion and threatening social/political development. False information …
influencing public opinion and threatening social/political development. False information …