The baseline model allowed a satisfactory accuracy of 99% for the given dataset. Published in: 2021 IEEE International Conference on Services Computing (SCC).
This paper focuses on increasing the reliability of the news, concentrating on static analysis of written text intending to detect possible disingenuous ...
We introduce the idea of utilizing ensembles of Kernel Minimum Enclosing Balls to detect novel datapoints. To this end, we propose a novelty scoring methodology ...
Nov 17, 2021 · The baseline model allowed a satisfactory accuracy of 99% for the given dataset. Index Terms—machine learning, fake news, disinformation, fake ...
Nov 4, 2024 · Our research aims to investigate different techniques within machine learning, deep learning, and ensemble learning frameworks in Arabic fake news detection.
The main intention of this paper is to design and introduce an innovative false news recognition method using Meta-heuristic Searched-Ensemble Learning (MS-EL).
In order to address this issue, this study suggests brand-new methods based on machine learning (ML) and deep learning (DL) for the fake news identification ...
This study proposes a machine learning ensemble approach for fake news detection, with a view to comparatively evaluating the performance difference between ...
Oct 23, 2023 · Automating fake news detection system ... Examining the Robustness of an Ensemble Learning Model for Credibility Based Fake News Detection.
Missing: Disinformation | Show results with:Disinformation
This paper proposes an ensemble model (EGNN) that leverages Graph Neural Networks (GNNs) and text features to enhance the accuracy of fake news detection.
Missing: Disinformation | Show results with:Disinformation