How AI can moderate content + protect your brand

every minute, 240,000 images are shared on Facebook, 65,000 pictures are uploaded to Instagram, and 575,000 tweets are posted to Twitter.

A man wearing a suit holds a digital rendering of Earth surrounded by various icons in his hand to represent AI content moderation.

Simply put, user-generated content is posted in various forms daily, and moderating everything that comes up on your brand’s online platform can be overwhelming and tedious — unless you’re using AI content moderation. Don’t take advantage

AI can optimize the moderation process by automatically categorizing, flagging and removing harmful content.

To help you determine how your brand should leverage AI content moderation, let’s take a look at what content moderation is and the different AI technologies available.

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What is content moderation?

Types of Content Moderation

How AI Content Moderation Can Help Your Brand

It is common practice to apply these guidelines for AI content moderation.

Now that you know what content moderation is, let’s explore the different types of content moderation and how AI can play a role in enhancing the process.

Types of Content Moderation

To understand how to best use AI to moderate content, you first need to know the different types of content moderation.

pre moderation

Pre-moderation assigns moderators to evaluate your audience’s content submissions before making them public.

If you’ve ever posted a comment somewhere and it was restricted or delayed after approval, you’ve seen pre-moderation at work.

The purpose of pre-moderation is to protect your users from harmful content that could negatively impact their experience and your brand’s reputation.

However, the downside of pre-moderation is that it can delay interaction and feedback from members of your community due to the approval process.

post abstinence

With post-moderation, user-generated content is posted in real time and can be reported as harmful after it is made public. Once reported, a human moderator or content moderation AI will flag and remove content if it violates established rules.

reactive moderation

Some communities rely solely on their members to flag any content that violates the Community Guidelines or is disliked by most users. This is called reactive moderation, a common process in small, tight-knit communities.

With reactive moderation, community members are responsible for reporting inappropriate content to the forum’s administration, which includes community leaders or site operators.

Admins will then review the flagged content to see if it violates any rules. If admins confirm that content violates the rules, they will manually remove it.

distributed moderation

Distributed moderation involves community members voting on user-generated content submissions to determine whether or not the content can be submitted successfully. Voting is often done under the supervision of senior moderators.

One positive takeaway from distributed moderation is that the process encourages higher participation and engagement from the community. However, it can be risky for brands to rely on users to properly moderate content.

How AI Content Moderation Can Help Your Brand

It’s no secret that AI-powered tools like Available on HubSpot Can increase productivity and save marketers time. This is especially true when it comes to content moderation.

Filtering out large amounts of inappropriate, malicious, or harmful content can take a toll on you and your colleagues.

And relying solely on humans can leave room for human error or result in content lingering for an extended time before the content is finally removed.

AI content moderation can instantly remove or block a wide variety of content that conflicts with your brand. Below are some of the ways AI can optimize your content moderation.

AI content moderation for texts

Natural language processing algorithms can understand the meaning behind a text, and text classifiers can classify text based on content.

For example, AI content moderation can analyze a comment to determine whether the tone of the text indicates bullying or harassment.

Entity recognition is another AI technology that can moderate text-based user-generated content. The method finds and extracts companies, names, and locations.

AI can be used to track mentions of your brand and mentions of your competitors.

AI content moderation for images and videos

Computer vision, also known as visual-AI, is an area of ​​AI that is used to extract data from visual media to determine whether there is unwanted or harmful content.

Furthermore, natural language processing and computer vision can together analyze text within an image to detect any suggestive content, such as street signs or T-shirt slogans.

Both forms of AI content moderation can moderate user generated videos and photos.

AI content moderation for voice recording

Sound analysis is the technique used to evaluate sound recordings and their content. It combines a variety of AI-powered content moderation tools.

For example, voice analysis can transcribe a voice recording into text and run a natural language processing analysis to identify the tone and intent of the content.

In short, AI content moderation can evaluate user-generated content more quickly and more efficiently than manual processes.

This allows your marketing team to spend less time sifting through content and more time crafting your next marketing campaign.

Using AI to optimize your content moderation process also protects your audience, brand and team from harmful content, creating a more enjoyable experience.

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