A Generalized Cross-Dataset Machine Deep Learning-based Fake News Detection Model and Dashboard Software

This folder contains the source code along with training and testing datasets for a Fake News Detection Dashboard. The dashboard allows users to detect disinformation using six standard benchmark datasets.The front end, developed with Streamlit, provides an interactive interface for uploading files in CSV, PDF, or DOCX formats, and visualizes results using bar charts and word clouds. Its modular architecture separates data ingestion, preprocessing, model inference, and visualization, ensuring scalability and maintainability. The dashboard has been applied to multiple datasets, including EUvsDisinfo, EUvsISOT, EUvsIGF, FA-KES, George McIntire, and ISOT, enabling large-scale predictions, cross-dataset generalizability assessment, propagation analysis, and exploration of textual patterns contributing to disinformation.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-06
DOI
https://doi.org/10.5281/zenodo.18158666
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
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article

A Generalized Cross-Dataset Machine Deep Learning-based Fake News Detection Model and Dashboard Software

Sadam Hussain
Zenodo (CERN European Organization for Nuclear Research)
Misinformation and Its Impacts
article

A Generalized Cross-Dataset Machine Deep Learning-based Fake News Detection Model and Dashboard Software

Sadam Hussain
article en

Abstract

This folder contains the source code along with training and testing datasets for a Fake News Detection Dashboard. The dashboard allows users to detect disinformation using six standard benchmark datasets.The front end, developed with Streamlit, provides an interactive interface for uploading files in CSV, PDF, or DOCX formats, and visualizes results using bar charts and word clouds. Its modular architecture separates data ingestion, preprocessing, model inference, and visualization, ensuring scalability and maintainability. The dashboard has been applied to multiple datasets, including EUvsDisinfo, EUvsISOT, EUvsIGF, FA-KES, George McIntire, and ISOT, enabling large-scale predictions, cross-dataset generalizability assessment, propagation analysis, and exploration of textual patterns contributing to disinformation.

Zenodo (CERN European Organization for Nuclear Research)
Goldsmiths University of London (GB)
Openalex Percentile: Top 95%
Misinformation and Its Impacts
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