Projects-Developer / Fake-News-Detection-using-machine-learning Star 33 Code Issues Pull requests Full stack Fake News Detection using machine learning Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials news fake fake-news final-year-project fak...
In this work, we propose a novel approach for Fake News Detection by comprehensively mining the Semantic Correlations between Text content and Images attached (FND-SCTI). First, we learn image representations via the pretrained VGG model, and use them to enhance the learning of text ...
Extracting the importance of words in a sentence using TF-IDF can be an excellent approach for fake news detection. Common English stop words like “the”, “a”, and “is” are removed while cleaning the dataset. Naïve bayes have been used to train the model. Multinomial Naïve Bayes...
FND_Report.pdf README.md main_bigcn.py main_gcnfn.py main_gnn.py main_gnncl.py requirements.txt results.png Repository files navigation README Fake News Detection Overview This repo implement the Fake News Detection task using variations of graph neural networks (GNNs). We use tw...
This was another bad week for media trust, or would be, if the news media would fairly report its own unethical behavior. Sometimes my instincts serve me well. I have piles of New York Times articles lying around my office, all intended to be the basis of future posts. Back in October...
Although platforms like Facebook and Twitter allow for a quicker, wider and less restricted access to information, they also consist of a breeding ground for the dissemination of fake news. Most of the existing literature on fake news detection on social media proposes user-based or content-...
In experiments to curb fake news sharing, researchers found that directly reducing anger in the moment had little effect; but encouraging personal agency via advertisements boosted fact-checking. This article is part of our special reportThe dark side of AI innovation is superchargi...
. We employ traditional bag-of-words and more recent end-to-end neural network models, and evaluate them on eight—five smaller and three larger—fake news datasets. The experimental results show that one can attain considerably precise detection performance, in some cases even in the very ...
To this end, we propose a new fake news detection method based on CLIP contrastive learning and multimodal semantic alignment (SARD). SARD leverages cutting-edge multimodal learning techniques, such as CLIP, and robust cross-modal contrastive learning methods to integrate features of news-oriented ...
git clone https://github.com/kapilsinghnegi/Fake-News-Detection.git Navigate to the project directory: cd fake-news-detection Execute the Jupyter Notebook or Python scripts associated with each classifier to train and test the models. For example: python random_forest_classifier.py The code wil...