Classification of Misinformation in New Articles using Natural Language Processing and a Recurrent Neural Network

One of the first issues to address with these labels is the Misinformation in news articles has been one of the main inconsistency of scales used. For example, some labels are topics for discussion over the past few years. There have scaled from 0-3 in terms of level of misinformation, others been several organizations that developed methods for assessing are scaled in a binary manner with 0 and 1, and some have 4 reliability and personal bias of news coverage. In today's categorical values based on levels of media bias. So there is day in age, it is unnatural to arbitrarily trust the news quite a bit of processing that needed to be done to normalize outlets that claim to be truly objective and unbiased because everything and transform the qualitative variables into quantitative the term "bias" is relative. What one person perceives as variables.