Content Moderation: Types, Tools & Best Practices

User engagement is the key to building a thriving social community, and the key to a successful business is loyal, active customers—no matter your use case. But this reward comes with risk. While user-generated content (UGC) can be empowering, persuasive, and insightful, it can also be off-topic, spammy, hateful, harmful, or even criminal.

By moderating content and enforcing appropriate consequences for users who post text, images, and video that violate community guidelines, you can keep your users safe, increase trust, and protect your brand's reputation.

Moderating content can be complex, as you could combine different tools, methods, and hires to create your unique strategy. So, read on to learn how to identify and handle multiple content mediums needing moderation, the platforms and technology to help you do it, best practices, and more.

What is Content Moderation?

Content moderation is the process of monitoring, evaluating, and managing user-generated content (UGC) to ensure it aligns with your platform's community guidelines, legal requirements, and brand standards. It is the backbone of digital trust and safety, protecting users from harmful material such as hate speech, explicit imagery, harassment, scams, and misinformation.

Moderation can be proactive, reactive, manual, or automated depending on the platform's risk tolerance, audience demographics, and scale.

At its core, effective moderation helps maintain healthy online spaces where users feel safe, respected, and engaged. Whether you're running a chat app, social feed, gaming community, or video-sharing service, moderation is essential to reducing abuse, fostering user trust, and ensuring long-term platform sustainability.

Defining Sensitive Content

The scope of sensitive content needing moderation is broad and why and how your team should censor it can vary. One user may accidentally share personally identifiable information (PII) but, another might maliciously dox someone, which would require your team to not only remove the victim's personal information, but penalize the user who posted them, too.

To build a safe and trustworthy environment, it's important to clearly define what qualifies as sensitive content. Below are common categories, each of which can harm your users, disrupt conversations, and undermine your community if left unmoderated:

Threat: Comments designed to intimidate or scare another person.
Sexual Harassment: Comments and abusive behavior designed to sexually humiliate a person.
Moral Harassment: Comments and abusive behavior designed to morally humiliate a person.
Self Harm: Self-harm is the intentional act of causing harm to one's own body.
Terrorism: Threats of violence, causing death, injury, or hostage-taking.
Racism: Discrimination or prejudice based on race or ethnicity.
LGBTQIA+ Phobia: LGBTQIA+ community discrimination.
Misogyny: Discrimination or prejudice against women.
Ableism: Prejudice towards individuals living with disabilities
Pedophilia: Any comment that exhibits or promotes sexual attraction towards minors.
Insult: Disrespectful or abusive language targeting an individual.
Hatred: Insults aimed to injure an individual, group, or entity.
Body Shaming: Harm towards an individual's physical appearance or modifications.
Doxxing: Sharing personal information without consent for intimidation or revenge.
Vulgarity: Crude, offensive, or explicit language.
Sexually Explicit: Content containing explicit sexual references or material.
Drug Explicit: Any type of comment that talks about or encourages the use of drugs.
Weapon Explicit: Discussion about or encouraged use of arms and weapons.
Dating: Content soliciting romantic or personal relationships.
Reputation Harm: Comments intended to harm the reputation of an entity or an individual.
Scam: Posts originated in order to extort money from a user.
Platform Bypass: Attempts to circumvent platform rules or moderation systems.
Ads: Promotional messages that businesses or individuals.
Useless: Content that do not add to or enrich conversation.
Flood: Repetitive or spam content that overwhelms communication channels.
PII: Sharing their personal identifiable information (PII) online.
Underage User: Disclosure where a user admits to being underage.
Link: Comments containing a link to another page or site.
Geopolitical: Opinions relating to politics, especially international relations.
Negative Criticism: Unconstructive or hostile feedback targeting individuals or groups.
Terrorism Reference: Content discussing or referencing acts of terrorism or extremist activities.
Boycott: Protesting products or policies to force change.
Politics: Comments related to government, political parties, and political figures.

These examples of sensitive categories interrupt your user experience, dissolve trust within your community, and pull focus away from the purpose of your business. Your brand can reserve judgment on what UGC requires moderation depending on your audience and maturity level, but robust, adaptable moderation is non-negotiable.

Why is Content Moderation Important?

User engagement drives the performance metrics that mean the most to your business. Your in-app experience must create a safe and enjoyable environment users will want to reopen again and again. If they encounter trolls, bullies, explicit content, spam, or disturbing media, they will leave.

Having a plan on how to moderate content shared on your platform is vital to preserve your brand. Clearly defined protocols for when policies have been violated reduce legal exposure, minimize churn, and uphold user trust by ensuring consistent and transparent enforcement of your community standards.

The 4 Types of Content To Moderate

While the first medium that comes to mind might be written messages, UGC today also consists of images and videos, which require a different moderation approach. Let's explore the four variations of sensitive content and their unique moderation solutions.

1. Text

Depending on your platform's media capabilities, written text might be the only way for users to communicate and express themselves. The variety of ways to leverage text might seem overwhelming: forums, posts, comments, private messages, group channels, etc. Fortunately, it's a medium of content that AI and machine learning-based chat moderation tools have mastered at scale. Algorithms can scan text of different lengths, languages, and styles for unwanted content according to your moderation policies.

2. Images

In theory, identifying inappropriate images seems simple, but many nuanced factors are at play. For example, detecting nudity or explicit images in UGC might flag famous, innocuous artwork. Or, your image detection might fail to identify what one area of the world considers inappropriate dress or subject matter versus the U.S. To effectively moderate images on your platform, AI models are best used in tandem with human moderators and user reporting to give the most complete and contextual moderation experience.

Advanced models now incorporate Optical Character Recognition (OCR) to detect harmful text embedded within images like hate symbols, PII, or otherwise. OCR identifies text within the image to detect and act on threats that would otherwise slip through traditional moderation policies.

3. Video

Video is another difficult type of content to moderate because it requires more time to review and assess the media. Text and images simply need a glance and the occasional additional context. But, a video could be hours in length and flagged for the content of only a few frames, requiring more time spent by your moderation team on a single case.

Video can also require text-based and audio moderation for inappropriate subtitles or recordings. However, while challenging, you must vigilantly guard your platform against harmful multi-media UGC. Your business will lose user trust and credibility if you tolerate community guideline violations.

4. Audio

Audio moderation involves managing voice messages, live audio streams, podcasts, and other spoken content. It presents unique challenges, such as detecting inappropriate language, harassment, or sensitive information.

Tools like automated speech recognition (ASR) and natural language processing (NLP) can transcribe and analyze audio for harmful content, while human moderators provide context for nuanced cases. For example, when someone uses a phrase like, "Oh, you're really going to wear that?". It may pass through ASR or NLP engines, but human moderators will be able to detect the sarcasm and mocking tone as harmful and take the appropriate action. Addressing these challenges ensures a safe and respectful environment for all users engaging with audio content.

4 Ways to Moderate Unsafe Content

1. Pre-Moderation

This method holds content before it appears on the platform for human review. While effective, pre-moderation is a time and labor-intensive strategy. It is best suited for platforms with vulnerable audiences that need high levels of protection, like those frequented by minors.

2. Post-Moderation

Post-moderation is a good fit when your business's audience is more mature and promotes user engagement. It permits users to publish content immediately and simultaneously adds it to a queue for moderation.

Historically, this moderation strategy was highly manual and limited scale, as a team member must review and approve every comment, post, thread, etc. However, modern AI-powered moderation has dramatically increased efficiency. The AI Models will intelligently prioritize content reducing moderator workload, shortening response times, and enabling teams to focus on cases that truly require human judgement.

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3. Reactive Moderation

This method combines user reporting efforts with moderation team review and assessment. In a typical reactive moderation flow, a user posts content, and another community member flags it for review if they find it offensive or in breach of community guidelines.

The primary benefit of this strategy is that your moderators save time by only reviewing content that users have designated as needing moderation instead of having to assess every piece of UGC. The risk of implementing a reactive strategy is that users might fail to flag harmful content and let it remain on your platform, damaging your reputation and eroding users' trust.

4. Automated Moderation

Automated moderation combines various ML and AI tools to filter, flag, and reject UGC of all types. These solutions can range from blocklists and filters to block IP addresses and algorithms trained to detect inappropriate images, audio, and video. Automated moderation can adapt to fit any type of use case and streamline your trust and safety process.

Best Practices for Moderating User-Generated Content

Establish & Socialize Community Guidelines

Define the rules of posting UGC on your site to inform users of the environment you want to create for your community. Think about your brand's personality and audience when drafting your rules; the more mature your user base is, the less stringent your guidelines might need to be.

Post your content rules somewhere easily accessible within your platform and require new users to read through and agree to follow the guidelines before engaging with others. This will ensure that if a user violates the rules, you have a record of them consenting to follow them and an argument for removing them from your community.

Set Violation Protocols

Defining fair and rational consequences of content violation is a vital step when creating a safe, positive social community. Your protocols on what actions to take when a piece of content requires moderation must be well-defined for transparency's sake among your users and your moderation team.

Violation protocols should define moderation methods, how to review content by medium, how to assess user-reported content, when to ban a user, a guide to initiating legal recourse, and what moderation tools are at your team's disposal. Publishing your business's violation protocols is as important as the community guidelines.

Leverage Moderation Platforms

Automating certain aspects of your moderation strategy can lighten the load for your moderation team and user base while ensuring your community maintains a high level of safety. Most moderation solutions can be easily integrated with your service and won't interrupt performance or user experience.

Moderation tools come with varying levels of sophistication and content-medium specialties to fill the gaps in your moderation team's skill set, like assisting in language translation. You must identify the moderation functions you'd like a tool to solve before you can narrow the field to your top choices.

Understanding AI-Powered Content Moderation

Machine Learning algorithms remove the burden of content moderation from trust and safety teams. They are trained using large datasets of previously flagged content to learn the signs of harmful, inappropriate, or off-topic UGC.

A detailed understanding of these parameters enables automated moderation tools to accurately flag, block, mute, ban, and censor multimedia content from users who violate community rules.

Ready to Build Your Trust & Safety Team?

Regardless of your content moderation method, you'll need to consider building a trust and safety team to support your strategy and serve as a resource to your brand's community. The members of this moderation team should be familiar with your community guidelines, understand how to enforce violation consequences correctly, get to know your audience, and feel comfortable managing any automated moderation tools you choose to leverage.