An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP
Overview
- Neural fake news (fake news generated by AI) can be a huge issue for our society
- This article discusses different Natural Language Processing methods to develop robust defense against Neural Fake News, including using the GPT-2 detector model and Grover (AllenNLP)
- Every data science professional should be aware of what neural fake news is and how to combat it
Introduction
Fake news is a major concern in our society right now. It has gone hand-in-hand with the rise of the data-driven era – not a coincidence when you consider the sheer volume of data we are generating every second!
Fake news is such a widespread issue that even the world’s leading dictionaries are trying to combat it in their own way. Here are two leading lights in that space taking a stance in recent years:
- Dictionary.com listed ‘misinformation’ as their Word of the Year in 2018
- Oxford Dictionary picked ‘post-truth’ as their Word of the Year a few years ago
