Content moderation solutions safeguard online platforms against misinformation, hate speech, and illegal and violent content. This helps in building trust, revenue, and growth for the platform.
Moderation services use various methods and setups to meet the specific needs of the online platform. They rely on a blend of AI and manual review.
Text Moderation
Text moderation involves monitoring and assessing user-generated content on text-based platforms, such as blogs, comments, reviews, and posts. It can be done manually or with the help of automated technologies and human moderators. It also includes screening images and videos for inappropriate language and imagery.
Some text moderation services use natural language processing algorithms to analyze the meaning and tone of the content. They can identify emotions such as anger, sarcasm, or negativity. They can even detect slang and profanity. They can also identify keywords that are related to certain topics, such as politics or sports.
The best text moderation service will allow you to filter content based on your specific requirements. For example, if you need to screen for particular terms that are considered to be offensive or illegal, you can create a custom term list. The API will respond with a list of the detected terms along with their location in the text.
Some text moderation services also offer features such as linguistic analysis, image recognition, and entity recognition. This allows them to scan for sensitive material such as sex, violence, drugs, and terrorism. This type of text moderation is ideal for websites that allow open interaction from their audience, such as matchmaking portals, e-commerce sites, and news platforms. This can prevent your website from becoming a forum for hate speech, bullying, or insults to symbols and beliefs held in high esteem by some groups of people.
Visual Moderation
When businesses host online communities, they must ensure that their users can interact safely. Otherwise, they risk losing user trust and creating negative associations with the brand. Moderation is crucial to any UGC, including text (like comments, forum posts, reviews, and ratings), photos, videos, audio, and links.
User Content is incredibly prolific and varied, making it challenging for human moderators to keep up with. Using AI to improve the moderating process can reduce the number of high-consequence cases that require human decision-making. It can also save a significant amount of time and resources by automating routine tasks.
With the help of VISUA, you can implement a robust visual content moderation solution. This service identifies and removes images, videos, and text that violate a platform’s guidelines and rules. This significantly reduces the volume of questions that need to be reviewed by humans and enables companies to maintain compliance without sacrificing quality.
AI-powered visual content moderation is a great way to ensure that your business or community can continue growing and engaging its users while protecting their safety. Computer vision and natural language processing can evaluate images for unwanted or harmful content, and voice analysis can analyze audio for suggestive language.
Users who experience disturbing, offensive, or unsafe content are more likely to leave a site or community. Moreover, they may share this information with others, creating negative associations with your brand or product. As such, it’s vital that you have a scalable content moderation process in place.
Live Streaming Moderation
Streaming video has emerged as a novel online community where thousands of users (viewers) entertain and engage with a broadcaster (streamer). However, these communities are plagued by toxicity in the form of harmful content like hate speech, cyberbullying, and sexual/racist abuse. To mitigate these occurrences, platforms employ automated tools and human moderators (either paid or volunteer) to enforce community guidelines.
Although the majority of moderators interviewed were happy with their moderation experiences, some felt burnt out by the amount of time and energy they put into their role. The responsibilities of the job can also become emotionally taxing, especially when faced with difficult or distressing comments. This can lead to the feeling of guilt or frustration that the moderator could have done more to prevent the occurrence, which in turn can erode their morale and commitment to their team.
Most moderators interviewed did not have formal training on how to moderate but felt they had acquired their skills through experience in other online communities, such as online forums or audio chat rooms. Others had backgrounds in teaching, customer service, or law enforcement. They had also learned through trial and error how to establish informal guidelines for their community. Regardless of the moderation method used, it is important to build a team of trusted moderators who are familiar with your community guidelines, understand how to implement violation consequences, and are comfortable managing any automated moderation tools that are leveraged.
Crowdsourcing Moderation
With content moderation services, you can keep user-generated content flowing to your site or app while weeding out offensive language, threats of violence, and sexually explicit material. A dedicated team of trained moderators will be your brand advocates to make sure users don’t experience damaging or threatening content on your platform.
Using an intelligent combination of AI and professional human teams, you can ensure that submissions meet your specific predefined policies and nuanced guidelines. This two-step process starts with an advanced machine-learning algorithm that is informed by both external data and your previous approval or rejection decisions. It then looks for blatantly inappropriate content and flags it for review by your expert moderators.
The next step involves your moderation partner’s live teams reviewing any remaining images, video, and text submissions based on your very specific and nuanced content guidelines. Their experienced human moderators will be able to identify patterns that the machine may not have yet learned to recognize.
A crowdsourced moderator is unlikely to understand your content guidelines and will likely not be able to separate off-brand content from acceptable content. They are also more likely to be biased by their own personal values, which can lead to a variety of problems. For example, some people will flag anything that doesn’t align with their own personal beliefs as “profane” or “explicit” to generate clicks and revenue.