Factfinder Rnn-Lstm Based Fake News Detection System Data In Cloud

Abstract

This paper presents an RNN-LSTM based fake news detection system to address the escalating problem of misinformation in the digital age. By leveraging Recurrent Neural Networks (RNNs) with Long Short- Term Memory (LSTM) units, the system effectively analyzes the sequential nature of textual data to distinguish between real and fake news. Through preprocessing, word embedding, and training on a labeled dataset, the model learns to identify patterns that indicate the authenticity of news articles or statements. The proposed system offers a promising solution to combat fake news, contributing to the promotion of reliable information dissemination in today's media landscape.