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Oct 26, 2022 · Fake News Detection Model using TensorFlow in Python Fake News means incorporating information that leads people to the wrong paths. It can have real-world adverse effects that aim to intentionally deceive, gain attention, manipulate public opinion, or damage reputation.
Jan 30, 2022 · In this paper, we propose a novel deep neural framework for fake news detection. We identify and address two unique challenges related to fake news: (1) early fake news detection and (2) label shortage. The framework has three essential parts: (1) news module, (2) social contexts module and (3) detection module.
Fake News Detection is a natural language processing task that involves identifying and classifying news articles or other types of text as real or fake.
This repo is a collection of AWESOME things about fake news detection, including papers, code, etc.
Fake News Detector* A deep learning network developed by CBMM computer scientists that detects patterns in the language of fake news.
May 1, 2023 · Currently, fake news detection relies mainly on news and context information. In this survey, we categorize factors that can aid fake news detection into seven categories of features: network-, sentiment-, linguistic-, visual-, post-, user-, and latent-based features. Download : Download high-res image (1MB) Download : Download full-size image ...
Jan 1, 2022 · Fake news detection aims to identify the fake news automatically. Existing traditional ML based FND methods require feature engineering. According to the features that the models utilized, those methods can be broadly divided into three categories: linguistic features, temporal-structural features and the hybrid features.
Apr 1, 2021 · The recent achievements of deep learning techniques in complex natural language processing tasks, make them a promising solution for fake news detection too. This work proposes a novel hybrid deep learning model that combines convolutional and recurrent neural networks for fake news classification.
Jun 24, 2024 · Detecting and neutralizing fake news in several languages can help to protect the integrity of global elections, political discourse, and public opinion. The lack of a robust multilingual database for training the classification models makes detecting fake news a difficult task. This paper looks at it by describing several forms of fake news (like serious fabrications, large-scale hoaxes, stance news, deceptive news, satire news, clickbait, misinformation, rumour). ...
Oct 26, 2023 · The automatic detection of social media related fake news has thus emerged as a highly anticipated research area in recent years. This paper offers a comprehensive review of the automatic detection of fake news on social media platforms.
