In the current digital era, the speed and scale of information dissemination are experiencing explosive growth. Various internet platforms, social media channels, online media sources, and more generate massive amounts of content daily. This content includes text, images, audio, video, and various other formats. It is estimated that, with images as an example, over 3 billion pictures are uploaded to the internet each day.

However, within this immense volume of content creation, it is inevitable that inappropriate information may appear. Examples include pornography, violence, terrorism, and other illegal content. These negative contents could potentially mislead the public, infringe upon the rights of others, and even lead to legal disputes. Without proper review and management, it will impact user experience and decrease user trust. This could potentially lead to the application’s removal, ultimately affecting the platform’s development and survival.

Hence, content moderation has become essential for protecting user rights and fostering the healthy development of the app content ecosystem.

AI Content Moderation is Gradually Replacing Traditional Manual Review

Traditional manual content moderation methods have various limitations. Firstly, manual moderation is slow and faces challenges in handling a massive volume of content moderation requirements. As the content volume expands, manual moderation necessitates a substantial allocation of human resources and time, resulting in decreased efficiency. Secondly, manual moderation is prone to subjective biases, resulting in varied reviewer standards and inconsistent review outcomes. Moreover, manual moderation is subject to fatigue over extended durations, consequently reducing accuracy of the review.

AI content moderation is efficient, accurate, and stable. It has become the predominant approach for moderating content. By leveraging advanced technologies like machine learning, deep learning, natural language processing, and computer vision, it handles vast content volumes. This significantly boosts review efficiency and reduces costs. Furthermore, intelligent algorithms can enhance review accuracy and consistency by continually learning and refining, thereby reducing misjudgments and oversights.

ZEGOCLOUD integrates advanced AI content moderation capabilities into its real-time interactive core products. This creates comprehensive content moderation and security compliance solutions.

How ZEGOCLOUD AI-Infused Content Moderation Solution Enhance Content Ecosystem Health

High Accuracy and Comprehensive Recognition

Concerning text risk identification, ZEGOCLOUD’s moderation system recognizes risk labels in 18 languages, adapting to varied regulations. Incorporating FastText, HMM, CRF, Word2Vec, the algorithm excels with over 99% accuracy. Utilizing the FSA algorithm, it detects variants, safeguarding against rule-evading content. Moreover, it extends recognition to emojis, effectively countering hidden harmful content.

The content moderation system excels in recognizing audio content. It identifies semantic violations in 18 major languages, including English, Arabic, Hindi, Indonesian, Vietnamese, French, and Japanese. This coverage ensures compliance with regulations in 90% of countries and regions, bolstering the global presence of the app. It recognizes various violation types, such as pornography and political content. This aligns with the standards of regulatory bodies and app stores. Leveraging semantic analysis, it detects nuances like moaning. It considers factors such as tone, melody, volume, and voiceprint, ensuring full adherence to content guidelines.

In addition, this moderation system showcases outstanding proficiency in spotting potentially harmful content present in image and video files. Notably, it excels in detecting text violations embedded within images using OCR technology. This effectively thwarts common violations, such as text insertion for advertising or abusive intents. Furthermore, it autonomously identifies explicit nudity, violent extremism, and political sensitivity. It also recognizes QR codes and other visual components, proficiently intercepting inappropriate content across various entertainment applications.

Multi-dimensional Auditing and Contextualized Strategies

Across various applications, scenarios, regions, and user perspectives, the definitions and standards for violations can vary significantly. Collaborating with partners, we developed a three-tier auditing tag system for various media content types, including visual, textual, and audio. The first-tier tag represents the violation category. The second-tier tag involves intent analysis logic. The third-tier tag provides detailed explanations of violations, including severity judgments. For example, for an inappropriate pornographic image, the applied tags could be: pornography (1st tier), sexual harassment (2nd tier), and severe sexual harassment (3rd tier). Alternatively, it could be categorized as: pornography (1st tier), products (2nd tier), adult items (3rd tier). This adaptable approach empowers clients to tailor audit focus and intensity based on regional policies and platform nuances.

We also enable flexible, scenario-specific strategies. Within the same app, content requirements vary based on different scenarios. This includes live streaming visuals, real-time voice chats, user avatars, group chat audio, and private chat audio. Corresponding auditing strategies can be adjusted as needed. In such cases, specific content sources can be designated during audit initiation. This is done by defining content sources and their respective tagging strategies. Subsequently, the auditing module identifies the relevant source markers. It activates the corresponding strategies to enforce different levels of scrutiny for the same content across various scenario types. For instance, an image may be considered inappropriate as a profile picture but permissible in private chats. Furthermore, support is available for region-based configurations, user-level specifications, and more.

Visualized Content Moderation Operations Console

The content moderation operations console is enhanced by custom content repositories. These repositories offer tailored text, audio semantics, and image text lexicons to complement standard audit tags. This customization enables precise blocking of items such as competitor names and regional cultural taboos. These items are often not identified as violations. Through an intuitive visual interface, operational staff can quickly review and correct content. They can extract audit records by tags and prioritize critical violation categories for review. This process optimizes the efficiency of human resource allocation.

AI Moderation and Effective Cost Control Capability

ZEGOCLOUD’s content moderation solution adopts a multi-dimensional approach to cost management. During initial integration, it provides advanced access solutions and sample code for audio, video moderation, and instant messaging review. This reduces development expenses and speeds up application rollout.

In day-to-day operations, optimizing the end-to-end process from submission to review trims moderation service costs. It also decreases submission and operational review expenses. This approach helps enterprises enhance content security and control in a comprehensive and cost-effective manner.

Defense Capabilities Against Illicit Industries

Many applications incorporate user acquisition rewards and promotional incentives to drive growth. As a result, safeguarding against illicit activities is a crucial consideration. The profit chain of such activities is ultimately closed through user actions like registration, gifting, task completion, and withdrawals. Therefore, the essence of anti-illicit activities products lies in assessing the risk level of user behaviors. They provide specific protective measures, with the core objective of identifying and preventing risky behaviors.

ZEGOCLOUD can tailor identification solutions based on the client’s business status, personalized by anti-illicit activities experts to balance cost-effectiveness. Additionally, by utilizing multi-dimensional features to build efficient threat detection capabilities, we assists developers in reducing business continuity disruptions and significant operational risks caused by security and compliance issues.

Minors Protection: ZEGOCLOUD’s Mission and Application

Despite variations in content rating systems and laws across different regions, the emphasis on protecting minors remains consistent. Whether it involves content featuring minors or content accessible to underage users, strict constraints are in place, covering prohibited content like obscenity, pornography, abuse, and violence. Compliance with these requirements directly determines whether an app can be successfully launched and operated continuously.

Reviewing app content is a critical aspect of protecting minors online. Platforms must promptly detect and address content risks involving minors, such as child pornography and pedophilia. Simultaneously, they should use intelligent recognition to assess the presence of minors among users, preventing their exposure to content that exceeds age-based ratings. Establishing corresponding content recommendation and filtering mechanisms is essential to create a safe online space for minors.

As a leading service provider with years of experience in the fields of entertainment, content socialization, and education, ZEGOCLOUD has accumulated strong technological capabilities and a comprehensive ecosystem of services. Its compliance services feature a full-cycle compliance guarantee process, including risk monitoring, anti-fraud measures, content moderation, and more, aiding platforms comprehensively in establishing a positive content environment and protecting the physical and mental health of minors.

Concerning the protection of minors, ZEGOCLOUD collaborates with professional partners to create a full-stack model and strategy system for intelligent analysis and recognition of platform content and user behavior across various dimensions like text, images, videos, and audio. By creating a comprehensive and distinctive system of content moderation labels for minor protection, precise determinations are made, intelligent recommendations are provided, content operation review processes are optimized, ensuring all-round compliance in business operations.

Within ZEGOCLOUD’s content moderation system, there are over 1800 refined content labels, with over 200 related to risks involving minors. These labels enable precise identification of violations in different regions, leading to over a 50% increase in efficiency for moderate personnel. The service allows flexible adjustments based on regional culture and local regulations, enabling the autonomous definition of moderation strategies to meet compliance requirements in diverse markets.

Conclusion

The AI content moderation products and safety compliance solutions offered by ZEGOCLOUD act as guardians in the digital age. Through ongoing advancements in technology and service quality, we will empower more enterprises to achieve their content security management objectives. This will assist clients in efficiently and cost-effectively maintaining a healthy content ecosystem. Contact us to get more details.