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Fake News Detection

17 papers with code · Natural Language Processing

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Defending Against Neural Fake News

29 May 2019rowanz/grover

We find that best current discriminators can classify neural fake news from real, human-written, news with 73% accuracy, assuming access to a moderate level of training data.

FAKE NEWS DETECTION TEXT GENERATION

Fake News Detection on Social Media: A Data Mining Perspective

7 Aug 2017KaiDMML/FakeNewsNet

First, fake news is intentionally written to mislead readers to believe false information, which makes it difficult and nontrivial to detect based on news content; therefore, we need to include auxiliary information, such as user social engagements on social media, to help make a determination.

FAKE NEWS DETECTION

Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder

17 Nov 2018david-yoon/detecting-incongruity

Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume.

DATA AUGMENTATION FAKE NEWS DETECTION INCONGRUITY DETECTION STANCE DETECTION

Learning Hierarchical Discourse-level Structure for Fake News Detection

NAACL 2019 hamidkarimi/DHSF

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

Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web

WS 2018 DeFacto/WebCredibility

To this aim, an important step to detect fake-news is to have access to a credibility score for a given information source.

FAKE NEWS DETECTION SUBJECTIVITY ANALYSIS WEB CREDIBILITY

Localization of Fake News Detection via Multitask Transfer Learning

21 Oct 2019jcblaisecruz02/Tagalog-fake-news

In this paper, we show that Transfer Learning (TL) can be used to train robust fake news classifiers from little data, achieving 91% accuracy on a fake news dataset in the low-resourced Filipino language, reducing the error by 14% compared to established few-shot baselines.

FAKE NEWS DETECTION LANGUAGE MODELLING TRANSFER LEARNING