# MEWS: Real-time Social Media Manipulation Detection and Analysis

arXiv: https://arxiv.org/abs/2205.05783 · HTML: https://mlsanity.com/paper/2205.05783/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 12 references that are in the map.
- First posted on arXiv 11 May 2022.

## Builds on (most cited first, 6 of 6)

- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [Sample and Computation Redistribution for Efficient Face Detection](https://mlsanity.com/paper/2105.04714/) (2021)
- [img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation](https://mlsanity.com/paper/2012.07791/) (2020)
- [Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election](https://mlsanity.com/paper/1707.00086/) (2017)
- [Propagation from Deceptive News Sources: Who Shares, How Much, How Evenly, and How Quickly?](https://mlsanity.com/paper/1812.03533/) (2018)
- [Automatic Discovery of Political Meme Genres with Diverse Appearances](https://mlsanity.com/paper/2001.06122/) (2020)

## Abstract (arXiv)

This article presents a beta-version of MEWS (Misinformation Early Warning System). It describes the various aspects of the ingestion, manipulation detection, and graphing algorithms employed to determine--in near real-time--the relationships between social media images as they emerge and spread on social media platforms. By combining these various technologies into a single processing pipeline, MEWS can identify manipulated media items as they arise and identify when these particular items begin trending on individual social media platforms or even across multiple platforms. The emergence of a novel manipulation followed by rapid diffusion of the manipulated content suggests a disinformation campaign.