Content Moderation Services in a Dynamic Digital World

The digital landscape grows, so does the volume of user-generated content (UGC). However, it's not always positive. Quite often instead of cheerful beautiful pictures we can stumble upon unpleasant, repulsive, and inappropriate content on social media platforms.

To ensure safe and enjoyable online experience for all, content moderation services come in to help monitor, filter, and control the content that is shared on the internet.

Meaning of Content Moderation

The implementation of content moderation ensures that offensive, obscene, or deceitful publications are removed promptly. Moderation also combats spam, trolling, phishing links, illegal content, and other forms of prohibited behavior. Modern social media platforms and websites where people can share their ideas and create user-generated content cannot exist without content moderation.

Content moderators help to create a safe space for users to express their ideas, opinions, and creativity without fear of encountering harmful online content. Inappropriate or offensive content can take various forms, ranging from hate speech and cyberbullying to graphic imagery and misinformation. These elements not only disrupt the positive dynamics of online communities but also potentially cause emotional distress and harm to users.

Most commonly, online platforms have community guidelines that every member of the community is obliged to abide by. Platforms are required to create and consistently apply their specific content moderation policies. Doing so will guarantee that users are informed of the rules, thus creating a fair and transparent environment. A lack of consistency in policy enforcement can lead to confusion and undermine trust in the platform's commitment to uphold a safe and respectful community.

Tasks and Goals of Content Moderation Services

Each social media platform has its own moderation rules, but the basic moderating tasks and goals remain the same.

Identifying and Removing Inappropriate Content

Content moderators are responsible for identifying and promptly removing content that violates community guidelines. Such undesirable data includes hate speech, harassment, graphic violence, or explicit material. Moderators oversee comments and user interactions across the platform, intervening when necessary to address inappropriate or harmful behavior, and fostering a positive online environment.

Implementing Age Restrictions

Moderators may enforce age restrictions by ensuring that age-sensitive or abusive content is not accessible to users who do not meet the specified age requirements. They track and filter content to ensure that it is age-appropriate information. Content moderation involves implementing parental controls that allow parents to set limits on the content their children can access. This feature allows a parent to manage their child's digital experience.

Providing Security

Content moderation protects users' personal information. By ensuring that no unauthorized sharing or misuse occurs, moderators contribute to the overall privacy and security of everyone in the digital space. From phishing attempts to online scams, content moderators are vigilant in identifying and preventing fraudulent activities that could exploit users. This helps to create a trustful and comfortable experience.

Maintaining Reputation and Brand Image

Content moderation aims to identify and address incidents of hate speech and harassment. Through proactive management of these issues, moderators contribute to the social platform's reputation of inclusivity and safety. In addition to the reputation of consumer brands and the platform itself, moderators can address incidents of online harassment and cyberbullying by actively monitoring interactions and comments, preventing damage to a person's reputation in digital communities.

Adhering to Regional Regulations

Content moderation implies a thorough knowledge of regional regulations governing the content of online resources. It assists compliance with legislation and monitoring violations. Social media networks are expected to comply with local and international laws related to copyright, personal data protection, human rights, and other regulations. Through awareness and adherence to these regulations, platforms ensure compliance with laws specific to the regions in which they operate. In cases where legal action is required, content moderation teams cooperate with law enforcement agencies.

Improving Customer Experience

Content moderation promotes a positive online environment by making sure that interactions, comments, and posts are in line with community rules. Such a positive atmosphere contributes to a more enjoyable and friendly experience. Content moderation establishes a safe environment for users to be able to express themselves online without fear of harassment or exposure to inappropriate content.

Moreover, content moderation encourages user engagement. While moderating content like comments and discussions, moderators create the kind of atmosphere where people are motivated to participate and socialize.

Types of Content Moderation

The following are the common types of content moderation. They can be classified by the type of moderator performing the moderation and approaches to content moderation.

By Moderator Type

There are 3 basic approaches to moderation:

Manual Moderation

This type of content moderation requires human moderators who take part in the process of verification of UGC on digital platforms. Such moderators, often in-house or outsourced, manually evaluate content to ensure that it meets community standards and guidelines.

As with all other types of moderation, human moderators have their pros and cons. Without a doubt, they bring a level of insight and contextual awareness that automated systems may struggle to attain, particularly in cases involving cultural nuances, sarcasm, humor, or subjective content.

However, as the flow of user-generated content increases, the use of this type of moderation alone becomes more problematic. As the number of subscribers and volume of content grows, manually moderating each entry becomes more demanding. Hiring and training a large staff of moderators to keep up with the demands can be challenging and expensive.

Automated Moderation

AI and machine learning are heavily employed to speed up and simplify the moderation process. Machine learning algorithms evaluate text, visuals, and audio within a small fraction of the time it would take humans to do it. Furthermore, AI cannot be psychologically affected by exposure to harmful content.

AI algorithms analyze user-generated content to identify patterns of illegal or inappropriate material by following predefined rules and guidelines set by platform administrators to make decisions about content moderation. This may include turning on and setting up profanity filters in the community settings. A list of forbidden words is fed into the algorithm. The system then flags the word, replaces it with another, or blocks or rejects the entire post.

As for the graphic content the system recognizes, deletes, or edits materials such as images, live streams, or videos by performing real-time monitoring.

Despite the ability to effectively scale to handle large volumes of UGC, automated systems typically lack the human judgment necessary to accurately assess content with cultural or context-specific components. Among other things, AI can generate false positives by mistakenly flagging content as offensive when it is not.

Therefore, automated content moderation cannot fully replace human oversight, especially in complex situations. This is why a combination of AI technology and the effort of human content moderators is commonly used.

Hybrid Moderation

Hybrid moderation describes an approach to content supervision that combines both automated moderation through the use of artificial intelligence and moderation carried out by humans. Simply put, it can be described as follows: AI screens the content, then controversial or challenging content is submitted to a human for evaluation.

Automated algorithms provide the scalability essential for handling massive amounts of content and apply rules consistently, while humans bring the necessary contextual understanding and the flexibility and adaptability to handle nuanced content.

By Moderation Approach

These types of moderation can employ either manual or automated content moderation tools, or the two combined:

Pre-moderation

In pre-moderation, user-generated content is vetted and approved or declined by content moderators before it becomes available to the public. It could be accomplished manually or with the help of automation. While this is one of the most reliable ways of blocking harmful content, it is a rather slow process and not applicable in the fast-paced online landscape.

Although it does an excellent job of maintaining a high standard of content quality by preventing inappropriate comments or harmful material from being displayed, content approval can introduce delays in its visibility, impacting real-time interactions on the platform.

Post-moderation

Post-moderation lets a user publish UGC on social media right away, however, it's moderated afterwards. Moderators examine posts or flagged content and take appropriate actions. Such an approach gives users an opportunity to post content in real-time, which encourages immediate engagement and interaction.

With a post-moderation approach users themselves often report content that breaches the social media policy. This kind of reporting mechanism helps platforms identify and address inappropriate or harmful content faster and more effectively. The main concern about post-moderation is the fact that inappropriate or toxic content may be exposed to the audience before it is deleted. This may result in negative user experiences, damage to the platform's reputation, and even legal consequences if the posted material breaches laws or regulations.

Reactive Moderation

Reactive Moderation entails self-regulation of an online platform by its participants. It may be applied on its own or implemented in conjunction with other, more reliable ways of getting rid of unwanted material.

Content moderation efforts are initiated in response to incidents or user reports, in addition to searching for unwanted content and its moderation by humans and/or automated systems. Content moderation efforts are initiated in response to incidents or user reports, instead of the active searching for unwanted content and its moderation. This approach requires moderators or algorithms to respond to specific issues, violations, or user reports. Reactive moderation may be utilized on its own or in conjunction with pre- and post-moderation.

The community's subscribers become responsible for the content that is shared in the community. The key benefit of this approach lies in the fact that it can be scaled as your community grows without putting additional strain on moderators. The more subscribers you have, the more users are keeping an eye on the community.

However, sometimes it can take a long time for unwanted content to be flagged by someone or not prevent all instances of inappropriate content at all. In addition, participants may abuse reporting mechanisms, leading to false positives or misuse.

Distributed Moderation

Distributed moderation refers to a relatively rare kind of moderation of UGC. It involves leveraging the collective efforts of a platform's user community in content moderation tasks. Unlike reactive moderation, this type of moderation means that the community will have complete control over the removal of undesirable materials on the site. That is, the moderation responsibility for the community rests solely on its members. Members of the platform actively participate in reporting, flagging, and sometimes even moderating content. It typically relies on a ranking mechanism that community members employ to vote on whether the content meets community policies.

It works like this, for example, if enough people vote against a certain post, the system removes or hides this material from the website. There are no designated moderators or AIs constantly seeking out and modifying inappropriate information on such sites. Such a system works well on websites where participants are highly involved in the project. However, the website owner cannot fully control what is moderated and what is not.

Even though it empowers users to actively shape the platform's content environment and gives them a sense of shared responsibility, some difficulties prevent this approach from becoming more widespread. The main challenge of distributed moderation is the fact that content moderation decisions may differ according to individual viewpoints, leading to consistency issues. On top of that, ensuring that the moderation decisions are valid and fair can be a difficult if not impossible task.

More frequently, platforms employ a mix of these moderation approaches to create a cohesive and successful content moderation strategy. There are advantages and challenges to each type of content moderation, and the choice often depends on the type of platform, the amount of user-generated content, and the level of oversight and engagement desired.

Content Moderation Tools

Diverse content moderation tools and platforms exist to cater to different needs and preferences. Some popular content moderation tools are listed below:

• Amazon Rekognition. It is an AI service that provides image and video analysis. It can be employed for content moderation, identifying explicit or suggestive content in images and videos;

• Hive Moderation. It offers automated content moderation solutions with a focus on achieving human-level accuracy. The tool supports the moderation of visual content, including images and GIFs, text and audio moderation;

• Respondology. This platform is specially designed to moderate content that contains racist remarks, insults, and other types of profanity. Such a targeted approach is valuable for brands and organizations striving to maintain a positive and respectful online environment;

• Text Moderation powered by PaLM 2. Text Moderation scans text content to identify and filter out potentially offensive or harmful material, actively working to create a secure online space. It filters and moderates text outputs generated by AI models, ensuring they adhere to ethical standards and do not produce content that could be offensive or harmful;

• Azure AI Content Moderation. It includes features for text moderation, image moderation, and video moderation. It can detect and filter content related to adult content, offensive language, and more.

Solutions that Simplify the Task of Content Moderation

Manual content moderation is an outdated and tedious process. When there is a lot of information, and the amount of user-generated content has multiplied manyfold in recent decades, manual human moderation alone is not just insufficient, it simply becomes ineffective.

Recently, this crucial task of maintaining a safe and positive online environment on online platforms has undergone a transformational change with the integration of artificial intelligence and machine learning into human moderation.

Toloka's Moderation Solution: AI Moderation with Human-in-the-loop Quality Control

Toloka's content moderation platform merges the efficiency of AI and machine learning with valuable human input. Offering an implementation in just one day, Toloka ensures a quick and efficient transition to automated content moderation, minimizing disruption to day-to-day operations and providing smooth integration of artificial intelligence technologies into the business process framework.

Toloka takes into account the diversity of user-generated content by offering moderation solutions for all types of data. This multifaceted approach enables companies to maintain a secure and inclusive online environment for different types of content. Content moderation solutions from Toloka include:

• Image moderation. Toloka's image moderation services are designed to identify and flag images that contain illegal content, such as images promoting violence, terrorism, or any other criminal activities, and images with adult themes. The solution also addresses copyright issues by identifying copyright-infringing images;

• Text moderation. The system monitors and controls written content, inspects and filters texts for such elements as hate speech, offensive and insulting language, and misleading content, intending to create a safer and more respectful cyberspace;

• Video moderation. In addition to addressing explicit or offensive material in various videos or live streams, video moderation also addresses copyright concerns by identifying and managing content that infringes on intellectual property rights. Moreover, Toloka's system seeks out and restricts content that violates social media policies or legal regulations;

• Audio moderation. The audio content in 13 different languages can be converted into written text using natural language processing techniques. The transcribed and processed text is then subjected to moderation which helps to identify and flag content that violates community rules or legal provisions, for instance, hate speech, explicit content, or any other prohibited material, etc.

Toloka's moderation system extends beyond basic analysis to detect explicit, implicit, or perceived threats of violence in advance. It improves security by allowing immediate action to be taken against undesirable content that hints at physical harm, aggression, or intimidation in texts, audio, or images and videos.

The solution excels at identifying and handling derogatory language. Toloka's solution is finely tuned to detect disrespectful, offensive, or hateful language directed at individuals or groups, ensuring that people are treated with respect. The platform also targets vulgar language and offensive expressions, maintaining a space free from inappropriate or indecent content and any kind of online harassment and cyberbullying.

Toloka's moderation solution involves protecting user privacy by identifying and dealing with sensitive or identifiable information about individuals, such as full names, addresses, telephone numbers, and other personal data.

In addition to the above-mentioned classes, it allows the recognition and concealment of nonsensical texts, explicit materials, spam advertising and promotions in any kind of content, be it visual, textual, or auditory.

Overseeing the Process of Moderation

Overseeing content moderation with Toloka's solution is easy, as there are several thoughtful solutions for this.

Convenient Statistics Panel

Toloka customers have access to an online dashboard that displays statistics related to content moderation. This panel presents an overview of moderation tasks by day, showing metrics such as the number of decisions made for processed content, the percentage of manual and automated moderation, the number of content moderation decisions approved and rejected, and other important data. Toloka's analytics feature allows a deeper insight into moderation results by providing visualized statistics organized by category.

The platform enables a user to fine-tune their moderation settings to increase accuracy. This can include manual moderation for ambiguous content and edge cases. By giving consumers the ability to set their own parameters, Toloka allows them to configure the moderation process based on the specific needs and nuances of the content in question. Besides, Toloka offers a user-friendly interface that can be accessed both online and on mobile devices.

Prompt Real-Time Monitoring

The Toloka platform offers real-time overseeing, allowing customers to observe and assess all comments in their social stream as they happen. This feature ensures that they stay up-to-date with the latest interactions and content moderation in real-time.

Access to a granular view of moderation results lets you get the details of what's being blocked and why. Toloka lets you dive into the details of moderation results so you know what's behind each comment that was blocked.

The moderation tool allows to categorize and sort those blocked comments by type. This categorization system helps in organizing and understanding the nature of the content being flagged or blocked. Users can group comments under different categories such as Racism, LGBTQ+ Slurs, Severe Swearing, etc.

Significance of Content Moderation Services

Wrapping things up, it's clear that content moderation is the backbone of our online experience. It makes sure that everyone has a good time online without getting traumatized in the process. From a business perspective, integrating content moderation services is about ensuring the longevity and sustainability of a brand in the digital scene.

Businesses and online communities gain significant benefits from implementing effective content moderation practices. Organizations build a positive brand image, user trust, and attract a wider audience by ensuring their platforms are free of offensive or unlawful content. Content moderation also contributes to legal risk mitigation and adherence to regulatory requirements by keeping platforms operating within acceptable guidelines.

Especially in a world where digital communication shapes perceptions and influences decision-making, companies that focus on content moderation are not just addressing reputational risks. They build the basis for lasting success in the constantly changing online landscape.