6 Essential Image Moderation Techniques for Online Platforms
The rise of digital platforms has made image-sharing commonplace. Images can express ideas, emotions, and stories in a way that words often can't. But with the power of images comes the potential risk of misuse. Inappropriate or harmful images can easily tarnish a platform's reputation and user experience.
This is where image moderation steps in. In this guide, we'll explore six essential techniques for effective image moderation.
Images are great tools for communication. They can convey a lot of information and emotion, often more efficiently than text.
When users post pictures on your site, they're not only adding content. They're also influencing how people see your brand. If a bad image gets through, it could harm your brand's image and make people leave your platform.
So, image moderation is not a nice-to-have feature, but an essential part of any online platform.
To maintain a safe and welcoming environment, effective image moderation has several techniques. Each technique has its strengths and can target specific types of problematic content.
Image labeling is a technique that involves categorizing or tagging an image based on its content. AI image labeling uses machine learning algorithms to analyze and classify images into predefined categories. This could include labels like nudity, violence, or alcohol, among others.
These labels are used to moderate content by either blocking, flagging, or alerting moderators about potentially inappropriate or harmful content. For example, if an image is tagged with 'nudity', and nudity is against the platform's rules, the image can be automatically removed or flagged for further review.
Example: Image labeled with potential nudity
Optical Character Recognition, or OCR, is a technology that converts different types of documents, such as scanned paper documents, PDF files, or images captured by a digital camera, into editable and searchable data.
In the context of image moderation, OCR can be used to extract text from images, which could be hiding spam messages, offensive language, or inappropriate comments. Once the text is extracted, it can be moderated just like any other text content, helping to ensure that harmful content doesn't slip through in image form.
Example: Image containing text
Image similarity is a technique that involves comparing an image to a database of other images to find matches or near-matches. Every image gets a unique digital fingerprint, or 'hash', of an image, which can be quickly compared to the hashes of other images.
This technique is particularly useful for identifying and blocking repeated offensive content or spam, as the same or similar images can be automatically flagged or blocked.
Example: Comparison of similar images with simalar hash
Custom AI models are machine learning models that are trained on a specific dataset – in this case, images from your platform.
By labeling these images (i.e., indicating whether they're appropriate, inappropriate, or fall into certain categories), the AI model learns to recognize and categorize new images based on what it has learned.
This allows for a high degree of customization and can enhance the accuracy and effectiveness of your image moderation efforts, as the model will be tailored to the specific types of images it will encounter on your platform.
Certain websites are known for hosting harmful or inappropriate content. To proactively guard against this, you can block images that are linked from these specific URLs.
This involves maintaining a blacklist of URLs associated with bad content, and any images linked from these sites are automatically blocked. This method is particularly effective for preventing known harmful content from entering your platform.
Despite the advancements in AI and machine learning, there are times when human judgment is necessary. This is where human moderation comes in.
Images that the AI flags as potentially problematic, ambiguous, or those that fall into a gray area can be reviewed and moderated by a human team. This ensures that nothing slips through the cracks and that your users have the best and safest experience possible.
At Lasso Moderation, we understand the importance of image moderation in maintaining a safe and welcoming online environment. That's why we use all these techniques in our AI-driven moderation platform.
Our integrated image moderation system uses AI-based image labeling, OCR, image similarity detection, custom AI models, and have a easy-to-use dashboard for human moderation. We also proactively block known bad image content, further enhancing the safety of your platform.
Want to learn more about Content Moderation?
Learn how a platform like Lasso Moderation can help you with moderating your platform. Book a free call with one of our experts.