  Social media and messaging apps have become major communication platforms.
Multimedia contents promote improved user engagement and have thus become a
very important communication tool. However, fake news and manipulated content
can easily go viral, so, being able to verify the source of videos and images
as well as to distinguish between native and downloaded content becomes
essential. Most of the work performed so far on social media provenance has
concentrated on images; in this paper, we propose a CNN architecture that
analyzes video content to trace videos back to their social network of origin.
The experiments demonstrate that stating platform provenance is possible for
videos as well as images with very good accuracy.
