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fake-news's Introduction

Fake-News-Detection Bot and WebApp with Flask

Project created in Algorithm6.0 Hackathon at AIKTC college in 24 hours.

Team Mates:

  1. Swapnil More
  2. Divya Kapil
  3. Navjot Singh Rajput
  4. Mahitha BSL

Tech Stack Used:

  1. NLP
  2. Flask
  3. TelegramBot
  4. newsapi

Dataset is as below

News and its labels:

alt text

created this dataset using Newsapi()

Model applied

  1. TF-IFD
  2. Trained with PassiveAgressive Classifier

Related news findings

1. Extracted keywords from news using Textblob

  • Found Noun phrases
  • Fed them to newsapi() to find related news

2. Also display top trending news using newsapi()

TF-IDF explained

TF (Tag frequency)

Here frequency of a word occurence in a document determines its importance. Higher the TF, higher the importance.

IDF (Inverse Document Frequency)

Here frequenct of a word between the documents is calculated to find its triviality. If a words occurs frequently in all documents, them its importance is irrelevant.

This helps us to vectorize the labels with important details while training

fake-news's People

Contributors

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Stargazers

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