Project information
- Category: Data Analysis
- Reason: Group Project
- Project date: September, 2020
- Tech: Python, PostgresSQL, Supervised Machine Learning, OpenDatasets, Logistic Regression, AWS, SKLearn, Pandas, SQLAlchemy, Jupyter Notebook, Tableau
- Project Details:
1. Shawn's 'Fake News Analysis' Project Overview
2. Presentation PDF
Machine Learning - Fake News Analysis
Main Objectives
Our team selected Fake News as our final project topic. Fake News is defined as misleading or false information presented as a real piece of news. We're interested in fake news given the recent political climate and the recent increase in fake news. Social media has also made fake news more prevalent and easy to circulate to media consumers. We figured this topic would allow us to pick from many data sources and be interesting to research.
Analysis Questions:
1. How likely is a piece of news to be real or fake based on certain criteria like; Author, Site-URL, Article Type, and amount of Interaction?
2. Additionally, do certain criteria inputs have a higher likelihood of predicting whether a piece of news is real or fake?