# This photograph has been altered: Testing the effectiveness of image forensic labeling on news image credibility

arXiv: https://arxiv.org/abs/2101.07951 · HTML: https://mlsanity.com/paper/2101.07951/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jan 2021.

## Built on by (most cited first, 2 of 2)

- [Signals of Provenance: Practices & Challenges of Navigating Indicators in AI-Generated Media for Sighted and Blind Individuals](https://mlsanity.com/paper/2505.16057/) (2025)
- [Dataset of News Articles with Provenance Metadata for Media Relevance Assessment](https://mlsanity.com/paper/2506.09847/) (2025)

## Abstract (arXiv)

Despite the ubiquity and proliferation of images and videos in online news environments, much of the existing research on misinformation and its correction is solely focused on textual misinformation, and little is known about how ordinary users evaluate fake or manipulated images and the most effective ways to label and correct such falsities. We designed a visual forensic label of image authenticity, Picture-O-Meter, and tested the label's efficacy in relation to its source and placement in an experiment with 2440 participants. Our findings demonstrate that, despite human beings' general inability to detect manipulated images on their own, image forensic labels are an effective tool for counteracting visual misinformation.