Utilization of Multinomial Naive Bayes Algorithm and Term Frequency Inverse Document Frequency (TF-IDF Vectorizer) in Checking the Credibility of News Tweet in the Philippines

Neil Christian R. Riego, Danny Bell Villarba
5/30/2023
cs.CL

No confident code implementation found for this paper. 1 possible match can be shown below.

Abstract

The digitalization of news media become a good indicator of progress and signal to more threats. Media disinformation or fake news is one of these threats, and it is necessary to take any action in fighting disinformation. This paper utilizes ground truth-based annotations and TF-IDF as feature extraction for the news articles which is then used as a training data set for Multinomial Naive Bayes. The model has an accuracy of 99.46% in training and 88.98% in predicting unseen data. Tagging fake news as real news is a concerning point on the prediction that is indicated in the F1 score of 89.68%. This could lead to a negative impact. To prevent this to happen it is suggested to further improve the corpus collection, and use an ensemble machine learning to reinforce the prediction

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Automated Identification of Disaster News For Crisis Management Using Machine Learning

87% match2023

How Good Are SOTA Fake News Detectors

87% match2023

It's All in the Embedding! Fake News Detection Using Document Embeddings

85% match1 repo52023

Performance Analysis of Transformer Based Models (BERT, ALBERT and RoBERTa) in Fake News Detection

85% match2023

Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2021

85% match2022

MalFake: A Multimodal Fake News Identification for Malayalam using Recurrent Neural Networks and VGG-16

84% match2023

Cite this paper

@article{riego2023utilization,
  title  = {Utilization of Multinomial Naive Bayes Algorithm and Term Frequency Inverse Document Frequency (TF-IDF Vectorizer) in Checking the Credibility of News Tweet in the Philippines},
  author = {Neil Christian R. Riego and Danny Bell Villarba},
  year   = {2023},
  eprint = {2306.00018},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.00018v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2306.00018.svg)](https://codeofpaper.com/paper/2306.00018)

Discussion