| Challenge: | Recent studies show that automatic unreliable news detection models only use the article itself without resorting to fact-checking mechanisms. |
| Approach: | They propose to use a simple model as a difficulty/bias probe instead of a complex one . they observe a significant drop in accuracy for all models tested in a clean split . |
| Outcome: | The proposed model can achieve good performance by memorizing site-label mapping instead of modeling the real task. |
Similar Papers
A Survey on Predicting the Factuality and the Bias of News Media (2024.findings-acl)
Copied to clipboard
| Challenge: | a growing number of scholars are profiling entire news outlets to profile fake content . political bias detection is also an important topic, but the two problems have been addressed separately . |
| Approach: | They argue that media profiling should be based on factuality and bias together . they argue that it is difficult to fact-check every single suspicious claim or article manually . |
| Outcome: | The present level of proliferation of fake, biased, and propagandistic content online has made it impossible to fact-check every single suspicious claim or article, either manually or automatically. |
Predicting Factuality of Reporting and Bias of News Media Sources (D18-1)
Copied to clipboard
| Challenge: | a new study examines the factuality of news media and its biases . social media has democratized content creation and spread information online . |
| Approach: | They propose to characterize entire news media to predict factuality and bias . they experiment with news websites and a set of features derived from their content . |
| Outcome: | The proposed model shows that the features of news websites perform better than baseline . the results show that the feature types are important for fact-checking systems . |
Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts (2025.findings-acl)
Copied to clipboard
| Challenge: | Important efforts to characterize news media outlets in terms of their political bias and factuality are labor-intensive and prone to human biases. |
| Approach: | They propose a method that emulates criteria used by professional fact-checkers to assess the factuality and political bias of an entire outlet. |
| Outcome: | The proposed method improves on baselines and with multiple LLMs. |
Automatic Fake News Detection: Are Models Learning to Reason? (2021.acl-short)
Copied to clipboard
| Challenge: | Existing methods for fake news detection rely on reasoning . existing work has not explored the predictive power of isolated evidence . |
| Approach: | They investigate the relationship and importance of both claim and evidence in fact checking models. |
| Outcome: | The proposed model performs better on political fact checking datasets using both the claim and evidence. |
Annotating and Analyzing Biased Sentences in News Articles using Crowdsourcing (2020.lrec-1)
Copied to clipboard
| Challenge: | a lack of publicly available news bias datasets has hindered efforts to detect subtle biases in news articles. |
| Approach: | They propose a news bias dataset which contains sentences with bias labels . they propose to use the dataset to develop and evaluate methods for detecting news bias . |
| Outcome: | The proposed dataset can be used for analyzing news bias and for developing and evaluating methods for news bias detection. |
Automatic Detection of Fake News (C18-1)
Copied to clipboard
| Challenge: | a growing number of fake news detection tools are needed to identify trustworthy news sources. |
| Approach: | They propose to use two novel datasets to automate the identification of fake news . they propose learning experiments to build accurate fake news detectors . |
| Outcome: | The proposed algorithms achieve accuracies of up to 76% and compare them with other tools . the proposed algorithms are based on satirical news sources and fact-checking websites . |
Adapting Fake News Detection to the Era of Large Language Models (2024.findings-naacl)
Copied to clipboard
| Challenge: | a gap exists in understanding the interplay between machine-paraphrased real news, machine-generated fake news, and human-written real news . false information is easier to generate but harder to detect due to the bias of detectors against machine-generated texts . |
| Approach: | They propose a strategy to adapt fake news detectors to the era of large language models and AI-driven content creation . |
| Outcome: | The proposed detectors perform well on human-written articles but not vice versa . the proposed detector should be trained on datasets with lower machine-generated news ratio than the test set . |
A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis (2026.findings-acl)
Copied to clipboard
Muhammad Arslan Manzoor, Dilshod Azizov, Daniil Orel, Umer Siddique, Zain Muhammad Mujahid, Yufang Hou, Preslav Nakov
| Challenge: | a large-scale label set for media outlets from Media Bias/Fact Check (MBFC) is lacking in the field. |
| Approach: | They propose to use a large-scale label set to analyze outlets' representations . they also propose to evaluate embedding views and fusion strategies . |
| Outcome: | The proposed method achieves state-of-the-art results on ACL-2020 and establishes strong benchmarks on MBFC-2025. |
Fake News Detection Strategies under Dataset Bias: Using Large-scale Coarse-grained Labels (2026.eacl-srw)
Copied to clipboard
| Challenge: | Existing datasets differ substantially in content distributions and annotation policies, complicating fair evaluation and generalization assessment. |
| Approach: | They quantitatively analyze dataset bias across multiple public fake news datasets with different annotation granularities, including article-level and publisher-level labels. |
| Outcome: | The proposed approach improves detection performance under in-dataset and cross-data set evaluation settings. |
Discovering Biased News Articles Leveraging Multiple Human Annotations (2020.lrec-1)
Copied to clipboard
| Challenge: | Political propaganda and one-sided views can be found in the news and can cause distrust in media. |
| Approach: | They propose to annotate politically biased news articles by an algorithm annotated by domain experts and crowd workers and to compare them to crowd workers. |
| Outcome: | The proposed method compares domain experts to crowd workers and shows that bias can be detected automatically. |