A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation
Source abstract
Abstract
News media profiling is helpful in preventing the spread of fake news at the source and maintaining a good media and news ecosystem. Most previous works only extract features and evaluate media from one dimension independentl... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Computational and Text Analysis Methods · Misinformation and Its Impacts · Media Influence and Politics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (40)
Show source-provided references
1. Mimicking human verification behavior for news media credibility evaluation10.3390/app13179553 ↗
2. Mainstream value information push strategy on Chinese aggregation news platform: Evolution, modelling and analysis
3. No word embedding model is perfect: Evaluating the representation accuracy for social bias in the media
4. A multi-task learning framework using graph attention network for user stance and rumor veracity prediction
5. Joint rumour and stance identification based on semantic and structural information in social networks
6. DSMM: A dual stance-aware multi-task model for rumour veracity on social networks10.1016/j.ipm.2023.103528 ↗
7. A multi-task attention tree neural net for stance classification and rumor veracity detection
8. Joint stance and rumor detection in hierarchical heterogeneous graph10.1109/TNNLS.2021.3114027 ↗
9. Rumor verification on social media with stance-aware recursive tree
10. A weakly supervised propagation model for rumor verification and stance detection with multiple instance learning
11. Predicting factuality of reporting and bias of news media sources
12. What was written vs. who read it: News media profiling using text analysis and social media context
13. P. Carragher, E. M. Williams, and K. M. Carley, “Detection and discovery of misinformation sources using attributed webgraphs,” 2024, arXiv:2401.02379.10.1609/icwsm.v18i1.31309 ↗
14. Sentence-level media bias analysis informed by discourse structures
15. GREENER: Graph neural networks for news media profiling
16. Tell me who your friends are: Using content sharing behavior for news source veracity detection
17. Tackling fake news detection by continually improving social context representations using graph neural networks
18. Partisan bias in the identification of fake news10.1016/j.tics.2021.05.001 ↗
19. Fine-tune longformer for jointly predicting rumor stance and veracity
20. Modeling conversation structure and temporal dynamics for jointly predicting rumor stance and veracity
21. SSRI-Net: Subthreads stance-rumor interaction network for rumor verification
22. A domain-adaptive pre-training approach for language bias detection in new
23. CAF-ODNN: Complementary attention fusion with optimized deep neural network for multimodal fake news detection10.1016/j.ipm.2024.103653 ↗
24. Multi-modal fake news detection on social media via multi-grained information fusion
25. POLITICS: Pretraining with same-story article comparison for ideology prediction and stance detection
26. Belittling the source: Trustworthiness indicators to obfuscate fake news on the web
27. Reliability estimation of news media sources: Birds of a feather flock together
28. Hounsel et al., “Identifying disinformation websites using infrastructure features,” 2020, arxiv:2003.07684.
29. Y. Kai-Cheng and M. Filippo, “Large language models can rate news outlet credibility,” 2023, arXiv:2304.00228.
30. Credibility perceptions and detection accuracy of fake news headlines on social media: Effects of truth-bias and endorsement cues10.1177/0093650220921321 ↗
31. Analyzing biases in perception of truth in news stories and their implications for fact checking10.1109/TCSS.2021.3096038 ↗
32. Attentional feature fusion
33. HorNet: Efficient high-order spatial interactions with recursive gated convolutions
34. Attention-based BiLSTM fused CNN with gating mechanism model for Chinese long text classification
35. AMFF: A new attention-based multi-feature fusion method for intention recognition10.1016/j.knosys.2021.107525 ↗
36. Research on short text classification method based on semantic fusion and BiLSTM-CNN
37. Network in network
38. Assessing the news landscape: A multi-module toolkit for evaluating the credibility of news
39. Robust fake news detection over time and attack10.1145/3363818 ↗
40. L. McInnes, J. Healy, and J. Melville, “UMAP: Uniform manifold approximation and projection for dimension reduction,” 2018, arXiv:1802.03426.10.21105/joss.00861 ↗