Fake News 📰

The idea is to develop a machine learning program to identify whether an article might be fake news or not.

Dataset link: https://www.kaggle.com/c/fake-news/data

train.csv: A full training dataset with the following attributes:

• id: unique id for a news article

• title: the title of a news article

• author: author of the news article

• text: the text of the article; could be incomplete

• label: a label that marks the article as potentially unreliable

  • 1: unreliable
  • 0: reliable

• test.csv: A testing training dataset with all the same attributes at train.csv without the label.

Plots for better understanding 📊

Counplot of the datapoints

This is the countplot for the datapoints belonging to a specific class.

From the above plot it is concluded that the dataset is properly balanced.

Distribution of Title length of the News

This the distibution of the Length of the Title of the News.

From the above plot we can conclude that most of the Titles for the News have a length between 10-20 words.

Distribution of Text length of the News

This is the distribution of the length of the Text in the News.

From the above plot we can conclude that the distribution is skew as the maximum number of datapoints lies below 2000 words.

Model Training

Accuracy vs Epoch Plot

Loss vs Epoch Plot