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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.

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chandnii7/Fake-News-Classification

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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: