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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.
Mar 14, 2023 · Fake news (i.e., false news created to have a high capacity for dissemination and malicious intentions) is a problem of great interest to society today since it has achieved unprecedented...
This repo is a collection of AWESOME things about fake news detection, including papers, code, etc.
Apr 14, 2023 · Content-Based Fake News Detection (CBFND) has the purpose of assessing news intention as a set of quantifiable features, often machine learning features, extracted from news content. CBFND is a critical tool for identifying news harmfulness.
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.
