Home // eKNOW 2022, The Fourteenth International Conference on Information, Process, and Knowledge Management // View article

Fake News Identification Using Neural Language Models

Authors:
Andrew Mackey
Susan Gauch
Jacob Fuller
Caden Williamson
Kate Pearce

Keywords: fake news classification; misinformation; neural language models; natural language processing

Abstract:
Given the widespread use of social media and other online platforms for sources of new content, there has been an increased interest in the research community to improve existing methods for automating the detection of fake news content. We present several models for automating the detection of fake news content while utilizing current state-of-the-art neural language models. Our work provides an evaluation of the efficiency of different transformer-based neural language models for the fake news detection task. The evaluation shows that the proposed models are able to maintain high accuracy (98.5%) throughout experimentation tasks. We conclude by discussing the effects of the different neural language models.

Pages: 81 to 88

Copyright: Copyright (c) IARIA, 2022

Publication date: June 26, 2022

Published in: conference

ISSN: 2308-4375

ISBN: 978-1-61208-986-7

Location: Porto,Portugal

Dates: from June 26, 2022 to June 30, 2022