Fetching the paper…
Reading the bibliography…
Both accuracy and timeliness are key factors in detecting fake news on social media.
Analyzing a portion of the roc curve
McClish D K · 1989
Earlier work this paper cites.
HowNet-a hybrid language and knowledge resource
Dong Z, Dong Q · 2003
Earlier work this paper cites.
Natural language processing with Python: analyzing text with the natural language toolkit
Bird S, Klein E, Loper E · 2009
Earlier work this paper cites.
Information credibility on twitter
Castillo C, Mendoza M, Poblete B · 2011
Earlier work this paper cites.
Fitnets: Hints for thin deep nets
Romero A, Ballas N, Kahou S E, Chassang A, Gatta C, Bengio Y · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Hinton G, Vinyals O, Dean J · 2015
Earlier work this paper cites.
Detecting rumors from microblogs with recurrent neural networks
Ma J, Gao W, Mitra P, Kwon S, Jansen B J, Wong K F, Cha M · 2016
Earlier work this paper cites.
The power of comments: fostering social interactions in microblog networks
Wang T, Chen Y, Wang Y, Wang B, Wang G, Li X, Zheng H, Zhao B Y · 2016
Earlier work this paper cites.
Hierarchical question-image co-attention for visual question answering
Lu J, Yang J, Batra D, Parikh D · 2016
Earlier work this paper cites.
Fake news detection on social media: A data mining perspective
Shu K, Sliva A, Wang S, Tang J, Liu H · 2017
Earlier work this paper cites.
Paying more attention to attention: improving the performance of convolutional neural networks via attention transfer
Komodakis N, Zagoruyko S · 2017
Earlier work this paper cites.
Understanding user profiles on social media for fake news detection
Shu K, Wang S, Liu H · 2018
Earlier work this paper cites.
A stylometric inquiry into hyperpartisan and fake news
Potthast M, Kiesel J, Reinartz K, Bevendorff J, Stein B · 2018
Earlier work this paper cites.
EANN: Event adversarial neural networks for multi-modal fake news detection
Wang Y, Ma F, Jin Z, Yuan Y, Xun G, Jha K, Su L, Gao J · 2018
Earlier work this paper cites.
Learning from context: a mutual reinforcement model for chinese microblog opinion retrieval
Wei J, Liao X, Zheng H, Chen G, Cheng X · 2018
Earlier work this paper cites.
DarkRank: Accelerating deep metric learning via cross sample similarities transfer
Chen Y, Wang N, Zhang Z · 2018
Earlier work this paper cites.
Word affect intensities
Mohammad S · 2018
Earlier work this paper cites.
dEFEND: Explainable fake news detection
Shu K, Cui L, Wang S, Lee D, Liu H · 2019
Earlier work this paper cites.
Beyond news contents: The role of social context for fake news detection
Shu K, Wang S, Liu H · 2019
Earlier work this paper cites.
Learning what and where to transfer
Jang Y, Lee H, Hwang S J, Shin J · 2019
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Devlin J, Chang M W, Lee K, Toutanova K · 2019
Earlier work this paper cites.
Mast fire probe amid 5G coronavirus claims, 2020
BBC · 2020
Earlier work this paper cites.
Capturing the style of fake news
Przybyla P · 2020
Earlier work this paper cites.
Early detection of fake news with multi-source weak social supervision
Shu K, Zheng G, Li Y, Mukherjee S, Awadallah A H, Ruston S, Liu H · 2020
Cited alongside, same era.
FNED: A deep network for fake news early detection on social media
Liu Y, Wu Y F B · 2020
Cited alongside, same era.
FANG: Leveraging social context for fake news detection using graph representation
Nguyen V H, Sugiyama K, Nakov P, Kan M Y · 2020
Cited alongside, same era.
GCAN: Graph-aware co-attention networks for explainable fake news detection on social media
Lu Y J, Li C T · 2020
Cited alongside, same era.
Contrastive representation distillation
Tian Y, Krishnan D, Isola P · 2020
Cited alongside, same era.
Heterogeneous knowledge distillation using information flow modeling
Passalis N, Tzelepi M, Tefas A · 2020
Dynamic probabilistic graphical model for progressive fake news detection on social media platform
Li K, Guo B, Liu J, Wang J, Ren H, Yi F, Yu Z · 2022
Later among the works it cites.
Unsupervised rumor detection based on propagation tree VAE
Fang L, Feng K, Zhao K, Hu A, Li T · 2023
Closest in time.
CNN-Fusion: An effective and lightweight phishing detection method based on multi-variant convnet
Hussain M, Cheng C, Xu R, Afzal M · 2023
Closest in time.
Meta-prompt based learning for low-resource false information detection
Huang Y, Gao M, Wang J, Yin J, Shu K, Fan Q, Wen J · 2023
Closest in time.
See how you read? multi-reading habits fusion reasoning for multi-modal fake news detection
Wu L, Liu P, Zhang Y · 2023
Closest in time.
Inconsistent matters: A knowledge-guided dual-consistency network for multi-modal rumor detection
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
FakeNewsNet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media
Shu K, Mahudeswaran D, Wang S, Lee D, Liu H · 2020
Cited alongside, same era.
Mining dual emotion for fake news detection
Zhang X, Cao J, Li X, Sheng Q, Zhong L, Shu K · 2021
Cited alongside, same era.
FakeBERT: Fake news detection in social media with a bert-based deep learning approach
Kaliyar R K, Goswami A, Narang P · 2021
Cited alongside, same era.
The mass, fake news, and cognition security
Guo B, Ding Y, Sun Y, Ma S, Li K, Yu Z · 2021
Cited alongside, same era.
Embracing domain differences in fake news: Cross-domain fake news detection using multi-modal data
Silva A, Luo L, Karunasekera S, Leckie C · 2021
Cited alongside, same era.
Integrating pattern- and fact-based fake news detection via model preference learning
Sheng Q, Zhang X, Cao J, Zhong L · 2021
Cited alongside, same era.
Sun M, Zhang X, Ma J, Xie S, Liu Y, Yu P S · 2023
Closest in time.
Causal inference for leveraging image-text matching bias in multi-modal fake news detection
Hu L, Chen Z, Yin Z Z J, Nie L · 2023
Closest in time.
Combating online misinformation videos: Characterization, detection, and future directions
Bu Y, Sheng Q, Cao J, Qi P, Wang D, Li J · 2023
Closest in time.
DHCF: Dual disentangled-view hierarchical contrastive learning for fake news detection on social media
Wang H, Tang P, Kong H, Jin Y, Wu C, Zhou L · 2023
Closest in time.
Rumor detection with self-supervised learning on texts and social graph
Gao Y, Wang X, He X, Feng H, Zhang Y · 2023
Closest in time.
Teachers cooperation: team-knowledge distillation for multiple cross-domain few-shot learning
Ji Z, Ni J, Liu X, Peng Y · 2023
Closest in time.
The challenges of machine learning for trust and safety: A case study on misinformation detection
Xiao M, Mayer J · 2023
Closest in time.
Memory-guided multi-view multi-domain fake news detection
Zhu Y, Sheng Q, Cao J, Nan Q, Shu K, Wu M, Wang J, Zhuang F · 2023
Closest in time.
It’s about time: Rethinking evaluation on rumor detection benchmarks using chronological splits
Mu Y, Bontcheva K, Aletras N · 2023
Closest in time.
Learn over past, evolve for future: Forecasting temporal trends for fake news detection
Hu B, Sheng Q, Cao J, Zhu Y, Wang D, Wang Z, Jin Z · 2023
Closest in time.
Multimodal matching-aware co-attention networks with mutual knowledge distillation for fake news detection
Hu L, Zhao Z, Qi W, Song X, Nie L · 2024
Closest in time.
Let silence speak: Enhancing fake news detection with generated comments from large language models
Nan Q, Sheng Q, Cao J, Hu B, Wang D, Li J · 2024
Closest in time.
DELL: Generating reactions and explanations for LLM-based misinformation detection
Wan H, Feng S, Tan Z, Wang H, Tsvetkov Y, Luo M · 2024
Closest in time.
Explainable fake news detection with large language model via defense among competing wisdom
Wang B, Ma J, Lin H, Yang Z, Yang R, Tian Y, Chang Y · 2024
Closest in time.
Bad actor, good advisor: Exploring the role of large language models in fake news detection
Hu B, Sheng Q, Cao J, Shi Y, Li Y, Wang D, Qi P · 2024
Closest in time.
Preventing and detecting misinformation generated by large language models
Liu A, Sheng Q, Hu X · 2024
Closest in time.
KD-Crowd: a knowledge distillation framework for learning from crowds
Li S, Zheng Y, Shi Y, Huang S, Chen S · 2025
Closest in time.