Fake News Detection using Machine Learning Project Report

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Description

Fake News Detection using Machine Learning Natural Language Processing . A NLP and Machine Learning based web application used for detecting fake news. Uses NLP for preprocessing the input text. Uses XGBoost model for predicting whether the input news is Fake or Real.

here are tons of stories articles, where the news is fake or cooked up. With numerous advances in tongue Processing and machine learning, we will actually build an ml model which is in a position to detect if a bit of stories … Here we’ll be using artificial neural network models to verify the genuinity of the article.

Table of Contents
Chapter 1 6
Introduction 6
Chapter 2 9
Related Work 9
2.1 Spam Detection 9
2.2 Stance Detection 10
2.3 Benchmark Dataset 11
Chapter 3 12
Datasets 12
3.1 Sentence Level 12
3.2 Document Level 13
3.3 Fake news samples 14
3.4 Real news samples 15
Chapter 4 17
Methods 17
4.1 Sentence-Level Baselines 17
4.2 Document-Level 18
4.3 Tracking Important Trigrams 18
4.4 Topic Dependency 22
4.5 Cleaning 24
4.6 Describing Neurons 26
Chapter 5 28
Experimental Results 28
5.2 Tracking Important Trigrams 31
5.3 Topic Dependency 31
5.4 Cleaning 32
5.5 Describing Neurons 34
Chapter 6 38
Discussion 38
6.1 Tracking Important Neurons 38
6.2 Topic Dependency 40
6.3 Cleaning 40
6.4 Describing Neurons 41
Chapter 7 42
Application 42
Chapter 8 43
Conclusion 43
8.1 Contributions 43
8.2 Future Work 44
Chapter 9 46
Appendix 46

 

 

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