User-generated content is not meant just for social media sites anymore. More and more organizations and companies in different sectors around the world are using AI-backed user-generated content. They have started realizing that content moderation solutions help in driving revenue and also build brand loyalty. Surveys indicate that more than 85% of people trust user-generated content over company-generated content.
Why consider content moderation?
Abusive and illicit content
User-generated content is not all about images and videos. There are multiple times when inappropriate and abusive language is used. On several occasions, offensive and abusive languages, images, and videos are reported on the internet. Henceforth, the importance to screen the content becomes so important. User-generated images, texts, and videos cannot be posted on social media pages and websites without undergoing stringent screening.
Reputation damage and liability issues
When any illicit content gets posted on the internet, the brand of a business gets affected tremendously. It is not just the reputation of the organization that gets damaged, but everyone associated with the business gets impacted, and liability issues emerge. For instance, child sexual exploitation content is illegal to be on servers.
Mental harassment for human moderators
Getting exposed to abusive and inappropriate content regularly causes mental hazards to human moderators. There are ongoing lawsuits over human content moderators experiencing PTSD and other mental distress due to the toxic content exposure on a day-to-day basis. Thus, the importance of content moderation solutions has become so critical for businesses with an online presence.
Types of content moderation
The five types of content moderation solutions are mentioned in the section.
Pre-moderation
It is the stage where content can be controlled before it gets posted on the internet. When a competent moderator evaluates, he/she ensures the inappropriate content is filtered out before posting. The superior control over what gets displayed on the internet, pre-moderation comes with a few downsides.
The content publication gets delayed, which can be a challenge in today’s world of instant gratification. In addition, the method is expensive as well as the content scales. It is mostly preferred by celebrities and kids’ communities as brand image and protection are vital.
Post-moderation
It is the stage where moderation and control can be incorporated after the content gets published. Such content moderation type can give a host of problems for companies and organizations. Damage to the reputation and brand image already takes place till the time illicit content is controlled and eliminated. From a legal perspective, the owner of the website, or social media page becomes the publisher of the content. Every piece of content that is viewed, rejected, or approved becomes a liability risk.
Reactive moderation
It is one such content moderation solution where the responsibility is on the user community to report and filter inappropriate content. It can be utilized alongside pre and post-content moderation solutions when things go past the human moderators. The prime advantage of reactive moderation is that one can scale with the growth in community members without exerting additional pressure on the moderation sources. In addition, one doesn’t need to increase the expense as well. One can avoid being liable for inappropriate content publication as long as the content elimination takes place within the acceptable time.
Distributed moderation
This is one of the less prevalent and used types of content moderation based on the audience reaction. It follows a self-moderated approach with a rating system. Content is posted or published on a website or a social media page directly. This is followed by a voting system by the users in the context of whether the content posted is apt and in compliance with community regulations. The users or audience are in control of the posts with the help of human moderators.
Automated moderation
Automated content moderation is the most common method used today. It uses natural language processing and AI. The AI-backed moderation solution can screen everything starting from texts, images, videos, and their combinations as well. One of the highlighting features of automated content moderation solutions is that multiple contents can be reviewed and flagged automatically faster than ever. Indecent and abusive content can be filtered out and prevented from getting published instantaneously. There is also greater accuracy with the support of human moderators.
The prime challenges for companies
The majority of the organizations face challenges in eliminating toxic and indecent content faster and instantly before it is seen. Thanks to the content moderation solution supported by AI (Artificial Intelligence) allows businesses with an online presence to scale faster and optimize the moderation solution so that there is more consistency for users. AI-backed moderation doesn’t mean there is no need for human moderators. They can offer ground truth evaluation and monitory for precision and manage more nuanced, and contextual issues. Different content demands different types of techniques and methods for moderation.
How do AI-backed moderations function?
Image moderation
For image moderation, image processing algorithms are used for identifying different areas inside the image and categorizing them based on the particular criteria. In addition, when there is textual content with the image, OCR (Object Character Recognition) identifies the offensive words or text and moderates the unstructured data.
Video moderation
While moderating videos, computer vision and AI methods are used. The videos need to be evaluated completely to verify the aptness of both audio and visual content. While moderating still images, shots are acquired at multiple intervals, and AI methods are used to verify the aptness of the content.
Text moderation
To understand the intention of the text, natural language processing algorithms are used. With the use of text classifications, categories can be allotted to assess the text with sentiments and emotions intended. For instance, the sentiment analysis can identify the tone of the text and categorize it as bullying, sarcasm, or anger, and even label it as positive, negative, or neutral.
Conclusion
The reality indicates that the current landscape of user-generated content is excessive for human moderators to keep up with. The AI-supported content moderation solutions are enabling companies and organizations to speed the review process with the exponential growth in the volume of user-generated content. Finding inappropriate content is faster and with more accuracy, thereby maintaining a safe and reputable business brand image.