AI Content Moderation: How AI Can Moderate Content + Protect Your Brand

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

Simply put, tons of user-generated content are posted in various forms daily, and moderating what finds its way to your brand’s online platform can be overwhelming and tedious — unless you leverage AI content moderation.

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

To help you determine how your brand should leverage AI content moderation, let’s walk through what content moderation is and the different AI technology available.

What is content moderation?

Types of content moderation

How AI Content Moderation Can Help Your Brand

It’s common for AI content moderation to implement these guidelines.

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 scaling the process.

Types of Content Moderation

To understand how best to 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 following approval, then you saw pre-moderation at work.

Pre-moderation aims to protect your users from harmful content that can negatively impact their experience and your brand’s reputation.

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

Post-Moderation

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

Reactive Moderation

Some communities rely solely on their members to flag any content that violates 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 platform’s administration, consisting of community leaders or whoever runs the site.

Administrators will then check the flagged content to see if it violates any rules. If the administrators confirm the content violates the rules, they will manually remove it.

Distributed Moderation

Distributed moderation consists of community members voting on user-generated content submissions to determine if the content can successfully be submitted. The voting is often done alongside the supervision of senior moderators.

A 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 trust users to moderate content appropriately.

How AI Content Moderation Can Help Your Brand

It’s no secret that AI-powered tools like the ones available at HubSpot can boost productivity and save marketers time. This is especially true when it comes to content moderation.

Sifting through 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 damaging content remaining public for an extended time before it’s finally taken down.

AI content moderation can quickly remove or block various forms of content that clash 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 decipher the intended meaning behind a text, and text classification can categorize text based on the content.

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

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

The AI can be used to track your brand’s mentions and your competitor’s mentions.

AI Content Moderation for Images and Videos

Computer Vision, also known as Visual-AI, is a field of AI used to extract data from visual media to determine if there is any unwanted or harmful content.

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

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

AI Content Moderation for Voice Recordings

Voice analysis is the technology used to evaluate voice recordings and their content. It combines several kinds of AI-powered content moderation tools.

For example, voice analysis could transcribe a voice recording into text and run a natural language processing analysis to identify the content’s tone and intention.

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

It 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, making for a more enjoyable experience.

The 4 Biggest Consumer Behavior Shifts of 2023 [According to New Data]

Your marketing strategy can’t stay stagnant if the people you’re selling to are changing their behavior — you have to adapt and learn how to cater to them. Marketers should look for observable differences in buyer behavior to continue meeting their needs.

To help marketers and other business professionals make more data-informed decisions, we’ve conducted a bi-annual survey of 600+ U.S. consumers to better understand how adults spend their money.

Using HubSpot Blog Research from our Consumer Trends Report, we’ll explore the nature of the biggest consumer behavior changes between May 2022 and January 2023 so that you can keep up.

Biggest Consumer Behavior Shifts

1. Consumers are warming up to purchasing products through social media apps.

In May 2022, only 12% of consumers preferred purchasing products through social media apps like Instagram Shop or Facebook Marketplace. In the past three months, 41% of social media users have shared that they feel comfortable purchasing on social media platforms.

That behavior shift is astounding. More than ever, social media marketers are more likely to impact consumer behavior by sharing content that builds interest and trust through these channels.

HubSpot Blog Research also found that the most popular social media platforms, Facebook, Instagram, YouTube, and TikTok, are the most preferred platforms for social shopping. Social shoppers also say Instagram and Facebook have the best in-app shopping experience.

These apps have very easy-to-use shopping interfaces, and it’s plain to see why they can sell or influence users. When consumers watch or interact with the content they enjoy and receive ads relevant to their interests, the products seem more valuable to their hobbies and lifestyles.

2. Gen X and Boomers are shopping through social media more, not just younger gens.

29% of Gen X (up 16% from May 2022) and 16% of Boomers (up 60%) say social media is their preferred product discovery channel. This shift is huge for generations that typically claim to prefer learning about products through TV ads and internet search.

Social media usage isn’t just something teens use every day. Older generations use it just as often. Social networking provides entertainment, community, and a more dedicated space for window shopping.

3. Support for small businesses isn’t dying down — it’s growing.

42% of consumers have chosen a product based on it being made by a small business in the last three months, up 8% from May 2022.

The later effects of the pandemic may be behind this behavior shift. Many consumers saw some of their favorite mom-and-pop shops close due to lost funds from decreased traffic and customers. Now that the worst of COVID is over, many consumers haven’t forgotten to support smaller businesses.

Another reason for supporting small businesses is the shopping experience itself. Many consumers enjoy shopping small due to:

Product diversity that chains don’t offer
More hands-on and personable customer service
The positive feeling of giving back and building a community

4. Consumers are shopping more consciously, supporting businesses with corporate responsibility.

Along with support for the local community, consumers are giving more of their money to companies that take a political stand on issues they care about. These three causes are among the most important to them:

Racial justice
Climate change initiatives
LGBTQ+ rights

Consumers want to support a company that pays it forward. They want to impact the world around them as they become more informed on news of global political unrest and other issues.

Businesses have much to gain from implementing socially responsible initiatives, programs, or donations to attract and retain customers. It may be the leading decision factor behind your next customer’s purchase between you and your competitor.

Keep Up with Consumer Behavior Trends

One of the most significant risks a marketing team can make is failing to adapt to changing consumer behavior shifts. Stay informed on your customers’ behaviors and ensure you meet their needs — even as they change.