Published June 6, 2017 | Version v1
Conference paper Open

Web Video Verification using Contextual Cues

  • 1. CERTH-ITI, Thessaloniki, Greece


As news agencies and the public increasingly rely on User-Generated Content, content verification is vital for news producers and consumers alike. We present a novel approach for verifying Web videos by analyzing their online context. It is based on supervised learning on contextual features: one feature set is based on an existing approach for tweet verification adapted to video comments. The other is based on video metadata, such as the video description, likes/dislikes, and uploader information.
We evaluate both on a dataset of real and fake videos from YouTube, and demonstrate their effectiveness (F-scores: 0.82, 0.79). We then explore their complementarity and show that under an optimal fusion scheme, the classifier would reach an F-score of 0.9. We finally study the performance of the classifier through time, as more comments accumulate, emulating a real-time verification setting.



Files (657.6 kB)

Name Size Download all
657.6 kB Preview Download

Additional details


InVID – In Video Veritas – Verification of Social Media Video Content for the News Industry 687786
European Commission