Content Moderation and Filtering Using Language Detection

Aleksandra Tadrzak
8 min read
Feb 5, 2024
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Most of us spend hours online every day without ever considering how content moderation shapes our experience. Everything you see while browsing the internet has had to pass through a content filter. The remarkable aspect of content moderation and filtering is that it is almost impossible to detect when it is done well. Conversely, even minor slip-ups in this area lead to glaring mistakes that can be easily spotted.

Without rigorous content moderation and filtering, the online experience becomes much riskier. Objectionable content like pornography could make its way onto platforms where sensitive audiences, such as minors, could view it. It could also lead to an increase in malware, fake news, and spam and a decrease in cybersecurity levels. 

Since the internet has no downtime, content moderation is a full-time job. In this article, we will look at how content moderation and filtering are crucial for businesses that manage online spaces for their customers and the newest tools available for this purpose.

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What is content moderation?

Content moderation is the process of regulating online content to promote a safe online environment for users.

Any online platform needs to be moderated, from comment sections under videos and articles to user-generated content like customer reviews. This protects the users from online abuse and harassment while allowing them to use virtual spaces without fear.

If there were no content filters in place, the wonderful World Wide Web as we know it would cease to exist. Most adult social media users in the U.S. (18 to 65 years old) believe that online platforms need stricter content moderation policies. The number of content takedowns across platforms supports these statistics. For example, between April and June of 2023, 18 million pieces of hate speech, 1.8 million  pieces of violent or graphic content, and 1.5 million pieces of bullying-related content were removed from Facebook! 

Depending on the manner of content moderation, there are several different approaches to filtering out harmful content online.

  1. Pre-moderation

This method involves moderating all online content before it is visible to users. This means that when a user posts content, the moderators must first approve it before appearing on the online platform. While this is ideal for businesses that wish to protect their brand from being associated with sensitive content, it also makes exchanging information on pre-moderated platforms time-consuming.

  1. Post-moderation

In this method, content is posted by users in real time, and moderators will only review and remove content if they find it necessary to do so. If a moderator sees problematic content on the platform or receives reports from users, they must act swiftly to take it down.

  1. Reactive moderation

Many online communities follow a reactive moderation approach, where users freely upload content. Moderators only step in when members start flagging content that violates the community’s guidelines. Reactive moderation is similar to post-moderation, except for how moderators can act independently in the latter but only respond to user reports in the former.

  1. Distributed moderation

This method operates like a popular rating system. Submitted content faces a vote, where community members decide whether it is appropriate for the platform or not. The results of this vote, along with moderator evaluation, determine the kind of content being uploaded to the platform. 

However, this method is only effective when used to moderate content for an active and engaged online community.

The internet is currently estimated to have 5.3 billion users. Out of that number, nearly 5 billion of them regularly use social media. That means billions of users post trillions, if not quadrillions, of megabytes of data online every day. That never-ending stream of data must be moderated for objectionable material, inaccurate information, and harmful malware.

The rise of AI content moderation and filtering

Content moderation and filtering are still performed manually on many online platforms. This approach has inherent drawbacks since human moderators can experience burnout and fatigue, make errors and oversights, and get swayed by personal biases. 

Also, the sheer volume of data posted online every day is simply overwhelming for human moderators. Fortunately, automation has become a boon to content moderators worldwide.

Artificial intelligence (AI) and its related fields, like machine learning (ML), natural language processing (NLP), and language detection, are invaluable assets when it comes to filtering and managing online content. AI moderation tools can perform the same tasks as human moderators but faster and at a much larger scale. The ways in which AI tools help online content moderation and filtering include:

The amount of data on the internet will only increase in the coming years. The World Economic Forum predicted that internet users would create 436 exabytes of data per day in 2025 (one exabyte = 1 billion gigabytes). 

Faced with this forever-growing mountain of data, AI content moderation and filtering tools are needed more than ever.

Language detection is an important AI content moderation tool

NLP grants computer programs and AI software the ability to interpret and communicate in a manner similar to humans. Language detection is a critical feature of NLP, especially when it comes to content moderation. 

Using language detection, AI moderation programs can use text categorization and their training data to accurately determine the language in which a piece of content was written. 

For example, hate speech needs to be removed from online platforms ASAP, regardless of whether it was posted in English or Spanish.

How content moderation works

There are two sides to effective content moderation. The first is reactive, involving AI or human moderators tracking objectionable content and taking it down. The second is proactive, involving setting guidelines and content filters (like blocklists or allowlists) that govern the nature of inbound content.

Strategies for effective content moderation and filtering

Whether using a manual, automated, or hybrid approach toward content moderation and filtering, following these best practices will help you manage content on your online platform much more effectively.

With all these helpful features, AI is ideally suited to take on the task of online content moderation in an increasingly data-dense world.

The pros and cons of AI content moderation

Any online platform where users can interact needs some form of moderation. The scope for harassment, abuse, and offensive messaging is just too high without it. While human moderators might overlook a violation of content guidelines for any number of reasons, AI content detection tools will not. The software will flag any content it has been trained to detect, offering platform users more impartial and unbiased enforcement of community guidelines.

Of course, there is always the risk of going too heavy-handed with AI content moderation. Excessive AI moderator participation in a community can stall conversations, detracting from the user experience and putting curbs on self-expression. 

Thankfully, as language detection features in AI software develop further, we’re not far off from a generation of AI tools that are capable of learning from every user interaction to develop a nuanced, community-specific approach to moderating content.

Why businesses need content moderation

There is no substitute for diligent, professional content moderation. Every business that maintains an online presence must allocate enough resources for content moderation and filtering or risk losing customers and visitors. 

The top benefits of investing in content moderation are listed below.

Protection against legal action

You could be held responsible for content that a third party posted on your platform. Content moderation ensures objectionable material stays off your platform, protecting you from any possible legal backlash.

Providing a safe environment for users

Harmful content drives users away from an online platform, which in turn hurts the business that hosts the platform. Effective content moderation gives users a safe space online that they will return to repeatedly, leading to the growth of a thriving online community.

Boosts brand reputation

Sometimes, harmful content doesn’t lead to legal action but can damage your brand reputation nonetheless. Active moderation ensures that all content on your platform is on-brand and that it doesn’t show your brand in a negative light.

AI content moderation in action

With approximately 430 million monthly active users, Reddit is one of the largest social media platforms. Users on Reddit congregate in groups called subreddits to upload and share content. While each subreddit is run by a team of human moderators, the website has also introduced an automated tool called AutoModerator. 

The AutoModerator can be customized and used at scale according to each subreddit’s requirements. Between the automated tools, human moderator team, and content reporting system, Reddit is one of the most ubiquitous examples of AI content moderation tools integrating smoothly into a hybrid content moderation approach.  

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In summary

Content moderation and filtering are essential ingredients of a safe and healthy online environment. Whether you’re relying on an in-house team or outsourcing it to a third party, the future of your online community depends on how well you tackle the challenges of content moderation and filtering.

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