Understanding Multi-Modal Content Moderation
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Multi-modal content moderation is the approach to moderate content in different formats — such as text, image, video, audio, or a combination of these formats — within a single framework.
Traditionally, content moderation techniques relied primarily on simple algorithms and human moderators. While these methods served their purpose at the time, they now have more obvious limitations. As digital platforms evolved, new content forms like images emerged.
The increased use of these diverse content types, often combined with one another, creates a demand for more complex and advanced moderation systems — this is where the new approach to multi-modal content moderation comes to light.
Here, instead of dealing with text-based and visual-based content, moderation is done separately. Multi-modal systems are meant to analyze them together and decide whether the content is safe. This approach should also improve the accuracy of the overall moderation system.
For example, a social media post may contain offensive text, paired with inappropriate images. A multi-modal moderation system solution will better evaluate both the image and text elements of posts together.
Understanding Multi-Modal Content Moderation for the Fooder app
As you’ll already know by now, the sample app used in this lesson, Fooder, is a social media app for recipes — users can post food recipes and, alongside this, see recipe photos, views, and comments over posts.