@inproceedings{4ac97997e7b04813b50e19ef6e689148,
title = "Not Everything You Read Is True! Fake News Detection using Machine learning Algorithms",
abstract = "This paper considers establishing if a news article is true or if it has been faked. To achieve the task accurately, the work compares different machine learning classification algorithm with the different feature extraction methods. The algorithm with the feature extraction method giving the highest accuracy is then used for future prediction of the labels of news headlines. In this work the algorithm show to have the highest accuracy was logistic regression with 71% percent accuracy when used with tf-idf feature extraction method.",
keywords = "Bag of words, k-nearest neighbor, machine learning, natural language processing, term frequency inverse document frequency",
author = "Vanya Tiwari and Lennon, {Ruth G.} and Thomas Dowling",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 31st Irish Signals and Systems Conference, ISSC 2020 ; Conference date: 11-06-2020 Through 12-06-2020",
year = "2020",
month = jun,
doi = "10.1109/ISSC49989.2020.9180206",
language = "English",
series = "2020 31st Irish Signals and Systems Conference, ISSC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 31st Irish Signals and Systems Conference, ISSC 2020",
}