Video content moderation
Moderate user-generated content and comply with official regulations by using ContentCore, WebKyte’s automaticcontent recognition software
Video content moderation
in the creator economy
In today’s digital world, where millions of people post videos on UGC platforms like YouTube and TikTok, monitoring these uploads is crucial. The objective is to ensure that these videos comply with the platform’s rules and policies, avoiding the display of any illegal content. This way video content moderation services lead to a safer, more welcoming environment for both viewers and creators.
What is video content moderation
Video content moderation is the process of monitoring, reviewing, and managing user-generated content on UGC platforms like video hosting and social media. The goal is to ensure that the content posted by users complies with the platform’s community guidelines, terms of service, and legal requirements. Moderation is crucial for providing a safe and more user – friendly experience for users and creators.
Use ContentCore to moderate video content at any scale by identifying and filtering out copyrighted, adult, and criminal materials. Check user-generated uploads for copyright and community guidelines violations, enabling automatic monitoring and removal of prohibited videos.
Powered by AI and video fingerprinting
Video fingerprinting is the technology that extracts distinctive elements of a video into a unique line of code, a digital fingerprint. The tech enables video matching at large scale, high speed, and with extraordinary accuracy.
As in most cases adjacent frames have only slight differences, it is not necessary to use every frame. The use of key-frames only reduces the size of the video fingerprint and, therefore, processing time.
- Lightweight
- High accuracy
- Built for scale
- Secure by design
Video content moderation in action
Discover the potential and impact of video content moderation technology in a wide range of use cases
- Filtering user-generated videosIdentify and filter out content that breaches the platform's guidelines, such as hate speech, violence, nudity, and other forms of explicit or harmful materials
- Live content moderationCheck live streams including live broadcasts, sports, concerts, etc. in real time for compliance with platform rules
- Prevent copyright infringementsAvoid illegal issues by respecting the copyright and proactively stoping illegal sharing of copyrighted videos
- Flag fake news and misleading contentControl the spread of fake news and misleading videos by instantly identifying copies of such videos across a platform
- Compliance with official regulationsComply with Article 17 EU, Digital Services Act EU, and other regulations by implementing a video fingerprinting solution
- AdvertisingProvide high-quality experience to advertisers by ensuring clean content for potential ad impressions
ContentCore features
ContentCore, an automatic content recognition software, improves video moderation activities by automating mass-scale video identification, filtering user-generated content, and ensuring compliance with copyright regulations.
Precise video matching
By using video fingerprints instead of video files, the process of content matching becomes significantly faster, delivering real-time results with near-zero false positives.
High accuracy
The usage of video fingerprints makes the probability of false positive results is nearly zero.
Built for scale
Video fingerprinting technology excels at handling large volumes of video content. It’s easier and faster to store and process compact representations of videos when it comes to massive amounts of data.
Secure by design
Video fingerprints are irreversible to the original files providing the highest level of content security. It’s impossible to identify the content without metadata.
Cost-effective
Automation of content recognition eliminates the need for extensive teams of analysts. A single content security professional can manage large amounts of content simultaneously.
Distortion resistant
Video fingerprints rely on video frames identifying content regardless of metadata, audio, and different distortions.
Supported video distortions
and video distortions
- Quality changes / CAMRip
- Dynamic zooming
- Slight rotation or cropping
- Interface elements, ticker, etc.
- Time inconsistencies such as playback
- Video fragments cut
- Mirroring
- Horizontal and vertical sidebars
- Logos and drawings overlays
- Color modifications
- Slight speed increase/decrease
- Deepfake