Fake News Tracker / Detection

Project Overview

Our topic is to analysis of fake news articles which recently has become a tremendous attention in the news media outlets. We will be comparing websites against lists of labeled fake news sources using Machine Learning approach. For our project, we will also use Natural Language Processing to detect fake news directly, based on the text content in the news articles from different sources.

Our Hypothesis

We want to develop a machine learning Model / Program which will identify from the news source which is or are producing fake news. We will build a classifier which will detect or make decisions about the information that were given in the news articles, we will be using multiple sources.

Hypothesis: The model will be able to predict whether an article contains fake news based on the multiple sources.
Null Hypothesis: The model was not able to predict whether an article contains fake news based on the multiple sources.

Data Set

Kaggle - https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset

Tools Used for the Project:

Machine Learning Model: Scikit-Learn, Tensorflow, Keras
Back end database: SQL Database
Front end: HTML, CSS, JavaScript
Connecting front end and back end: Python
Charts: JavaScript Libraries (Plotly)
Deploying Application: Heroku & GitHub Pages