DOAJ Open Access 2024

A Hybrid Computer-Intensive Approach Integrating Machine Learning and Statistical Methods for Fake News Detection

Livio Fenga

Abstrak

In this paper, we address the challenge of early fake news detection within the framework of anomaly detection for time-dependent data. Our proposed method is computationally intensive, leveraging a resampling scheme inspired by maximum entropy principles. It has a hybrid nature, combining a sophisticated machine learning algorithm augmented by a bootstrapped versions of binomial statistical tests. In the presented approach, the detection of fake news through the anomaly detection system entails identifying sudden deviations from the norm, indicative of significant, temporary shifts in the underlying data-generating process.

Topik & Kata Kunci

Engineering machinery, tools, and implements

Penulis (1)

Livio Fenga

Format Sitasi

APA MLA BibTeX

Fenga, L. (2024). A Hybrid Computer-Intensive Approach Integrating Machine Learning and Statistical Methods for Fake News Detection. https://doi.org/10.3390/engproc2024068047

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Informasi Jurnal

Tahun Terbit: 2024
Sumber Database: DOAJ
DOI: 10.3390/engproc2024068047
Akses: Open Access ✓