The Other Side of the Screen: 6 Types of Content Moderation and How They Affect Users and Moderators
The ill effects of current content moderation methods on both moderators and users are becoming regularly reported on by numerous news outlets. Moderators are overworked and constantly subjected to traumatizing content, while the state of users’ online safety continues to fluctuate across platforms. However, content moderation processes come in many shapes and strategies, and can be broken down into six different types that, when investigated, provide a sense of what is truly happening on the other side of your screen.
The 6 Content moderation methods:
Online platforms that are powered by user-generated content usually have an understanding of the content standards they want their community to adhere to. Creating community guidelines or content policies is foundational to steering users to post appropriate content for the platform. Needless to say, this is not sufficient on its own, and content moderation is necessary to start eliminating harmful, illegal, and otherwise guideline-violating content.
To work toward cultivating a safer online platform, content moderation is integral for identifying and removing said content, whether that’s through automated technology, a team of moderators, or both. Content moderation is not a one-size-fits-all approach, and there are different methods to keeping platforms safe.
Content Moderation Methods
1. Manual pre-moderation
Manual pre-moderation filters all user-generated content for approval before it goes live on the platform. This method provides full control over the content that goes out; a moderator can reject, publish, or modify the content before exposing it to other users.
The effectiveness of this method depends on moderators’ speed and the size of the team-to-content ratio. Evaluating each piece of content with a fine-tooth comb can become time-consuming and may pose problems for time-sensitive content and hinder the user experience.
Training content moderators to spot harmful content such as complex scams or misinformation can be costly, and requires consistent improvement. Performing manual pre-moderation for certain features could be much more ideal depending on the sensitivity of platforms’ main content types, e.g. children’s gaming platforms or dating websites.
2. Manual post-moderation
Manual post-moderation is when content goes live as soon as the user hits ‘post,’ then the content sits in a queue for a moderator to review. At the review stage, the moderator can make changes or remove the post as needed. Most large platforms allow users to post instantly and make content moderation secondary, as it adds to the quality of the user experience.
A side effect of manual post-moderation is exposing users to potentially harmful content before the content is reviewed and taken down by moderators. Since this method of content moderation leaves content visible for an indefinite amount of time before the manual moderation process, it can lead to many issues such as upset users, an influx of duplicate reports, and negative publicity.
3. Reactive moderation
Reactive moderation is a method that relies on users to report or flag content on the platform, where it is then sent off to content moderators to make the final decision to remove or modify the content. While this can be a strong force against guideline-violating content, it’s best to use reactive moderation as a supplement to other content moderation methods.
Reactive moderation is a cost-effective form of content moderation, though it doesn’t give much control over the platform’s content, with or without clear community guidelines. Reactive moderation leans heavily on the number of negative user experiences, which could hurt the platform’s brand image and user base.
Like manual pre-moderation, reactive moderation is a slower process. The more time harmful content stays live on the platform, the longer it takes for users to report, ultimately straining the workflow of a small team of moderators.
4. Distributed moderation
Distributed moderation is similar to reactive moderation; it leaves the community of users to determine what content is acceptable, helpful, or harmful. These kinds of platforms are based on voting systems where up-voted content is more visible and down-voted content is pushed to the bottom or hidden altogether.
For upcoming legislations that will regulate platforms for harmful content, in-scope platforms should steer clear of distributed moderation. This type of content moderation can be somewhat dangerous, as control over what content goes live is limited.
5. Automated and hybrid moderation
Automated content moderation is a technology-dependent method that uses tools or filters to identify harmful content. There is a large array of automated content moderation tools, from simple keyword catching, to AI, to hash-matching technologies, each used to analyze content and identify issues such as hate speech, spam, or nudity. Automated moderation tools can help online platforms manage the large volume of user-generated content more efficiently, and reduce the workload of human moderators.
However, complete automation of moderation processes is quickly becoming an unpopular method. Platforms who’ve relied heavily on automation report concerns about the accuracy and potential bias of automated moderation tools, as they may not always be able to understand the context of the content or detect subtle nuances of language. Therefore, many online platforms still rely on human moderators to make the final decision on whether to remove content or not. This joint method is called hybrid moderation.
Hybrid content moderation is a relatively new approach to content moderation that combines automated tools with human moderation. Automated tools are used to identify, flag, and automatically block potentially harmful content. The weaker of the matches deemed harmful are then reviewed by human moderators who then make the final decision on whether to remove the content or not. This approach allows for a faster and more consistent moderation process while still ensuring that human judgment is involved before take-down.
As mentioned above, an extremely helpful benefit of hybrid content moderation is that it can help address the scalability issues that many online platforms face when dealing with large amounts of user-generated content. Automated tools can quickly scan and flag potentially problematic content, allowing human moderators to focus on reviewing the most critical cases. This approach can also help reduce the workload for human moderators. Who, with the help of these technologies, can focus their attention on more complex cases that require human judgment.
6. No moderation
An online platform that chooses not to implement content moderation processes may face several negative effects, both for the platform and its users. Here are some potential consequences:
Spread of harmful and illegal content: Without content moderation, the platform is likely to become a hub for harmful and illegal content such as hate speech, harassment, misinformation, and illegal activities. This can create a toxic environment for users and damage the platform's reputation.
Decreased user engagement: Users are likely to abandon the platform if it becomes a haven for negative content. This can lead to decreased user engagement, lower user retention, and ultimately, reduced revenue for the platform.
Legal liabilities: Platforms that fail to moderate content may be held liable for illegal activities that occur on their site. This can result in lawsuits, fines, and other legal penalties.
Advertiser loss: Advertisers may not want to associate their brand with a platform that has a negative reputation. This can result in loss of revenue from advertising partnerships.
Trust and reputation damage: If the platform becomes known for hosting harmful and illegal content, it may damage the platform's trust and reputation, making it difficult to attract new users or business partnerships.
Choosing not to implement content moderation processes can have severe consequences for online platforms, including the spread of harmful and illegal content, decreased user engagement, legal liabilities, advertiser loss, and damage to trust and reputation.