About

Fake news detection is the task of detecting forms of news consisting of deliberate disinformation or hoaxes spread via traditional news media (print and broadcast) or online social media (Source: Adapted from Wikipedia).

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Datasets

Greatest papers with code

Fake News Detection on Social Media using Geometric Deep Learning

10 Feb 2019gordicaleksa/pytorch-GAT

One of the main reasons is that often the interpretation of the news requires the knowledge of political or social context or 'common sense', which current NLP algorithms are still missing.

COMMON SENSE REASONING FAKE NEWS DETECTION GRAPH CLASSIFICATION

Defending Against Neural Fake News

NeurIPS 2019 rowanz/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

r/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection

10 Nov 2019entitize/fakeddit

We construct hybrid text+image models and perform extensive experiments for multiple variations of classification, demonstrating the importance of the novel aspect of multimodality and fine-grained classification unique to Fakeddit.

FAKE NEWS DETECTION

Weak Supervision for Fake News Detection via Reinforcement Learning

28 Dec 2019yaqingwang/WeFEND-AAAI20

In order to tackle this challenge, we propose a reinforced weakly-supervised fake news detection framework, i. e., WeFEND, which can leverage users' reports as weak supervision to enlarge the amount of training data for fake news detection.

FAKE NEWS DETECTION

Some Like it Hoax: Automated Fake News Detection in Social Networks

25 Apr 2017gabll/some-like-it-hoax

As a contribution towards this objective, we show that Facebook posts can be classified with high accuracy as hoaxes or non-hoaxes on the basis of the users who "liked" them.

FAKE NEWS DETECTION MISINFORMATION