It's obvious that this phenomena is here to stay given the rise of user-generated content (UGC), which is now being used in a variety of sectors outside of social media.
Images, text, video, and audio are all included in UGC in the modern world. Future development of new forms is anticipated. Any company incorporating user-generated content into its strategy must have a system in place to manage the moderating process. There is no other method to guarantee a positive customer experience and reputation that are consistent with branding.
In the future, as your company grows, it will be crucial to pay attention to how you distribute your resources and labour. The most effective way to regulate material and keep scaling is through AI-powered automation under human supervision. Developing a content moderation AI strategy is crucial for achieving this.
This article intends to throw some light on the implementation of AI in the crucial process of Content Moderation.
AI-Powered Moderation
According to the statistics, there is a mismatch between the volume of UGC submitted online and the capacity of human moderators. This brings us to a solution for businesses looking to efficiently moderate their content, and that is content moderation automation.
Given their resources, businesses may scale more quickly through content moderation that uses AI to assist human moderators in their review process. The safety and comfort of community members as well as the overall reputation of your site depend on your ability to precisely detect and swiftly delete improper information.
Depending on the type of content, there are a variety of tailored AI content moderation techniques that can be applied.
AI-Powered Moderation for "Text" Content
To interpret the emotions in text and understand the intended meaning, Natural Language Processing algorithms are used. Text categorization enables the text or sentiment to be classified according to the content.
Sentiment Analysis, for instance, may determine the tone of a text and classify it as bullying, rage, harassment, sarcasm, etc. before classifying it as either positive, neutral, or negative.
Another AI content moderation method that removes names, places, and businesses is Entity Recognition. This type of content moderation AI technique can inform you of the frequency with which your business has been discussed on a specific website or even the proportion of reviewers who are local to a specific area.
The exact technology includes:
Natural Language Processing (NLP): Keyword filtering, which categorises keywords into groups like positive, neutral, and negative based on their emotional content, and subject analysis-based warnings delivered to the moderation team, are examples of possible actions here (for sensitive keywords that can imply crisis, brutality, and age-sensitive content).
Machine Learning: Computers can accurately detect information that is false news or a frequent scam by looking at historical databases.
AI-Powered Moderation for "Voice" Content
On this, we're looking at Voice Analysis, a field of technology that focuses on voice and its recognition. It makes use of a number of different AI-powered tools and can perform tasks like voice to text transcription, NLP, sentiment analysis, and even voice tone interpretation.
AI-Powered Moderation for "Image" Content
Image content moderation automation uses text classification alongside vision-based search techniques. The techniques involve the use of different algorithms that detect harmful images and then locate the particular harmful content’s position on the image.
Content Moderation AI for images makes use of image processing algorithms to recognise regions inside the image and classify objects based on a specified criterion. The entire content component can be controlled using Object Character Recognition (OCR) if there is text present in the image.
Computer Vision is a branch of AI that teaches machines to understand and interpret the visual world in order to recognise dangerous images. Any objectionable and upsetting content is understood, identified using tags, and, if necessary, sent to the moderation team by the AI content moderation.
AI-Powered Moderation for "Video" Content
The speech analysis, text, and picture technologies that were previously covered are combined in the automation of video content moderation.
Wrapping Up
You can examine content more quickly with content moderation automation than with manual operations. The pre-moderation approach has the significant advantage of processing massive amounts of data put online at any given moment while enabling community members to interact in virtually real-time.
As was said above, hundreds of thousands of pieces of content are posted to social media every minute, making the use of manual review methods to handle this exceedingly ineffective and uneconomical.
Users should be shielded from hazardous content while still being given the opportunity to engage in meaningful discussions, so data moderation should occur as quickly as feasible.
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