An Effective Hybrid Text-Based Approach to Identify Fake News on Social Media

Imtiez Fliss, Hamza Bargougui

2023

Abstract

Because of their low cost, simplicity of access, and quick dissemination, social media are today one of the primary information sources for millions of people worldwide. However, this is at the expense of dubious credibility and a large danger of being exposed to ”fake news,” which is deliberately designed to mislead readers. In light of this, in this paper we propose a novel method for identifying bogus news based on the text content. This method is founded on a mix of BERT (Bidirectional Encoder Representations from Transformers) and deep learning techniques (Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM)). Promising results are seen when the proposed approach is compared to other models.

Paper Citation

in Harvard Style

Fliss I. and Bargougui H. (2023). An Effective Hybrid Text-Based Approach to Identify Fake News on Social Media. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 374-380. DOI: 10.5220/0011674400003393

in Bibtex Style

@conference{icaart23,
author={Imtiez Fliss and Hamza Bargougui},
title={An Effective Hybrid Text-Based Approach to Identify Fake News on Social Media},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={374-380},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011674400003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - An Effective Hybrid Text-Based Approach to Identify Fake News on Social Media
SN - 978-989-758-623-1
AU - Fliss I.
AU - Bargougui H.
PY - 2023
SP - 374
EP - 380
DO - 10.5220/0011674400003393