Automated Content Moderation

In order to be effective, a platform moderation tool needs to strive for a high level of accuracy and operational precision. This is where Spectrum Labs’ Guardian AI excels.

When it comes to interpreting the nuance and context of content, human moderators often fall prey to their unconscious biases in the face of a frantic work pace and unrealistic productivity expectations.

Text Moderation

While the rules of conduct for an online community may vary by platform, flawless communication is key to building strong connections with your customers. Automated moderation tools like Spectrum Labs Guardian can help amplify the efforts of your human content moderation teams and create an outstanding experience for everyone in your community.

This solution utilizes Natural Language Processing (NLP) to identify potentially inappropriate text or personal information, enabling you to take action. We offer both simple and advanced labs using Amazon Comprehend, a managed Machine Learning service that offers pre-trained PII detection models for this use case.

To set up text moderation, you need to supply the system with training data. This should include examples of both harmful and positive behaviors, as well as a list of profanity words for filtering in multiple languages. Then, when users submit content, the system will run it against your behavior model and send back a response that includes a determination indicating whether or not forbidden content was detected along with a confidence score.

Image Moderation

Image moderation is the process of reviewing, analyzing and filtering photos, graphics or other visual content before publishing it. It includes checking images for explicit nudity, racy content, violence, drugs and alcohol use as well as other potentially harmful or offensive criteria.

If the UGC content of a website or application includes a lot of graphically disturbing images, it can damage a brand’s online reputation and diminish trust among its end-users. This is why it’s important for businesses to rely on a combination of automated content moderation tools and human moderators.

While image moderation is usually conducted manually, when the volume of NSFW images grows beyond a business’s capacity to manage it, Eden AI’s Explicit Content Detection API can help. This moderation tool uses computer vision in machine learning to automatically understand and analyze images, allowing it to quickly reject sexually explicit or otherwise harmful content. It also displays a risk level for each image along with a JSON response.

Video Moderation

A growing number of businesses are empowering their employees to create and share videos for collaboration. This has a number of benefits, including centralized knowledge sharing, improved productivity and increased employee engagement. But it also comes with some risks.

Moderation services can be used to detect and remove nudity, obscene or defamatory content from video submissions. This reduces the risk of these materials getting posted to your website or social media platforms and helps you maintain a clean online presence.

Video moderation is a complex task and requires the use of machine learning. There are a number of moderation services that utilize this technology, such as Amazon Rekognition. These are a great tool to help your human moderators, as they can identify offensive or inappropriate material with an 80% accuracy rate. You can also integrate them into your own platform by using a video moderation API. This will allow your team to work faster and improve their work by identifying the most problematic content automatically.

Social Media Moderation

As a result of the popularity of online social media platforms, there is a need for large-scale automated content moderation tools. These tools must be able to detect harmful speech in languages and communities that are not well-understood. Moreover, they must be able to do this in accordance with international human rights law.

The primary limitations of current social media moderation tools are their failure to detect and stop the spread of misinformation and hate speech. This has caused the platforms to be held accountable for inciting violent acts such as the January 6th, 2021 incident at the US Capitol building.

To address this challenge, it is important for the companies to adopt pre-moderation practices and use social media moderation solutions that are reliable. They must also ensure that human moderators are working in an environment that is safe and secure. Besides, they must have the right training and support to make the job easier.