chandnii7 / fake-news-classification

Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.

Fake News Classification

Given the title of a fake news article A and the title of a coming news article B, program classifies B into one of the three categories:

• agreed : B talks about the same fake news as A.
• disagreed : B refutes the fake news in A.
• unrelated : B is unrelated to A.

Basic preprocessing steps are required before using the data:

1. Convert to Lowercase
2. Remove punctuations
3. Remove single character if any
4. Remove stop words
5. Convert numbers to words
6. Lemmatization to get root words

Feature extraction approaches:

• Bag of words
• Similarity between text
• TF-IDF

Data modeling approaches:

• Naive Bayes
• Multinomial Logistic Regression
• Multi Layer Perceptron Classifier

Refer the report for further implementation details, approach, data preprocessing, feature extraction, data modeling and evaluation: View Report

Results: