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Fake News Detection

15 papers with code ยท Natural Language Processing

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Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection

4 Sep 2019

Recently, neural networks based on multi-task learning have achieved promising performance on fake news detection, which focus on learning shared features among tasks as complementary features to serve different tasks.

FAKE NEWS DETECTION MULTI-TASK LEARNING

Are We Safe Yet? The Limitations of Distributional Features for Fake News Detection

26 Aug 2019

One approach that has recently gained attention detects these fake news using stylometry-based provenance, i. e. tracing a text's writing style back to its producing source and determining whether the source is malicious.

FAKE NEWS DETECTION LANGUAGE MODELLING

Exploiting Multi-domain Visual Information for Fake News Detection

13 Aug 2019

In the real world, fake-news images may have significantly different characteristics from real-news images at both physical and semantic levels, which can be clearly reflected in the frequency and pixel domain, respectively.

FAKE NEWS DETECTION

Tensor Factorization with Label Information for Fake News Detection

11 Aug 2019

As the detection of fake news is increasingly considered a technological problem, it has attracted considerable research.

FAKE NEWS DETECTION

Gradual Argumentation Evaluation for Stance Aggregation in Automated Fake News Detection

WS 2019

One very important stage in employing stance detection for fake news detection is the aggregation of multiple stance labels from different text sources in order to compute a prediction for the veracity of a claim.

FAKE NEWS DETECTION STANCE DETECTION

BREAKING! Presenting Fake News Corpus for Automated Fact Checking

ACL 2019

Popular fake news articles spread faster than mainstream articles on the same topic which renders manual fact checking inefficient.

FAKE NEWS DETECTION

Fake News Detection using Stance Classification: A Survey

29 Jun 2019

This paper surveys and presents recent academic work carried out within the field of stance classification and fake news detection.

FAKE NEWS DETECTION FEATURE ENGINEERING

Deep Two-path Semi-supervised Learning for Fake News Detection

10 Jun 2019

News in social media such as Twitter has been generated in high volume and speed.

FAKE NEWS DETECTION

Fake News Detection using Deep Markov Random Fields

NAACL 2019

While the correlations among news articles have been shown to be effective cues for online news analysis, existing deep-learning-based methods often ignore this information and only consider each news article individually.

FAKE NEWS DETECTION

Learning Hierarchical Discourse-level Structure for Fake News Detection

NAACL 2019

Incorporating hierarchical discourse-level structure of fake and real news articles is one crucial step toward a better understanding of how these articles are structured.

FAKE NEWS DETECTION