A journalist's guide to verifying images

Oct 30, 2018 in Digital Journalism

Breaking news sometimes brings out people who want to fool the public with doctored images, so every journalist should know how to verify the authenticity of photos and videos.

Enter digital journalists Mandy Jenkins and Craig Silverman, who are perfecting the art of online verification.

Jenkins, social news editor for the Huffington Post, and Silverman, editorial director of OpenFile.ca and editor and author of Regret the Error, shared their advice during their presentation, "B.S. Detection for Journalists," at the recent 2011 Online News Association Conference in Boston.

Here are their tips for verifying images:

1. See what info is attached to the image in an exif (exchangeable image file format) viewer, such as this one.

2. Check for edits to photos. Use Image Level Analyzer, which uses photo quality to determine whether a photo has been altered. (Images saved as jpeg files lose quality each time they are saved. If someone has pasted part of one photo into another, different parts of the image will have different levels of quality.)

3. Reference the image's supposed location against maps and existing images from the area. Examine weather reports and shadows to confirm that the conditions shown fit with the claimed date and time.

4. Check clothes, building, languages, license plates, vehicles, signs and other elements of the photo or video to see if they support what the image claims to be.

5. Review the uploader's history and location to see if he or she has shared credible content in the past or may be "scraping" content from others.

6. Are there images the shooter took before and after the one you are trying to verifty that you can use as a comparison?

7. Get the shooter on the phone or Skype to talk about the image. People are less likely to lie to you when talking to you directly.

8. Beware of the amazing shot in a breaking situation. If it seems too good to be true, it probably is.

9. Use TinEye, a reverse image search engine, which “finds out where an image came from, how it is being used, if modified versions of the image exist, or if there is a higher resolution version,” according to the site.

The slides from Jenkins' and Silverman's complete presentation, "B.S. Detection for Journalists," can be viewed here.