# Check-It: A Plugin for Detecting and Reducing the Spread of Fake News   and Misinformation on the Web

**Authors:** Demetris Paschalides, Alexandros Kornilakis, Chrysovalantis, Christodoulou, Rafael Andreou, George Pallis, Marios D. Dikaiakos, Evangelos, Markatos

arXiv: 1905.04260 · 2019-05-13

## TL;DR

Check-It is a browser plugin that combines multiple signals to detect fake news efficiently, achieving over 99% accuracy on a large dataset while respecting user privacy.

## Contribution

It introduces a novel system that integrates various signals for fake news detection within a browser plugin, outperforming existing methods.

## Key findings

- Achieves over 99% accuracy on a dataset of 9 million articles.
- Outperforms state-of-the-art fake news detection methods.
- Operates efficiently as a privacy-preserving browser plugin.

## Abstract

Over the past few years, we have been witnessing the rise of misinformation on the Web. People fall victims of fake news during their daily lives and assist their further propagation knowingly and inadvertently. There have been many initiatives that are trying to mitigate the damage caused by fake news, focusing on signals from either domain flag-lists, online social networks or artificial intelligence. In this work, we present Check-It, a system that combines, in an intelligent way, a variety of signals into a pipeline for fake news identification. Check-It is developed as a web browser plugin with the objective of efficient and timely fake news detection, respecting the user's privacy. Experimental results show that Check-It is able to outperform the state-of-the-art methods. On a dataset, consisting of 9 millions of articles labeled as fake and real, Check-It obtains classification accuracies that exceed 99%.

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/1905.04260/full.md

## References

29 references — full list in the complete paper: https://tomesphere.com/paper/1905.04260/full.md

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Source: https://tomesphere.com/paper/1905.04260