Video games have become increasingly social. Players spend time with friends, meet new people, communicate, and build communities that can extend beyond a single match or session.

As those social interactions grow, so do the ways players can violate platform policies. That means trust & safety teams are managing a wider range of activity while preserving the experiences that bring players together.

Ahead of National Video Games Day tomorrow, we’re looking at how gaming platforms can approach some of those challenges as player communities become more active and connected.

Player authenticity starts at onboarding

Before players begin interacting with others, platforms may need to enforce age requirements and verify demographic attributes.

Demographic models can estimate attributes including age category, age regression, and gender from images and video. Those results can support age-gate enforcement and demographic verification, helping platforms recognize users who may fall outside age requirements and apply age-based restrictions.

AI-generated profile images can also be used to create fake accounts. AI detection models can help trust & safety teams identify synthetic profile images and flag them for further review.

Moderation has to keep pace with player activity

In-game chat, livestreams, and other player interactions can generate a constant flow of text, images, and video. Because policy violations can surface in real time, platforms need to detect them quickly.

Visual moderation models can identify categories such as NSFW, violence, drugs, and hate in images and video, along with more specific subclasses like weapons or blood. Those classifications can help trust & safety teams apply different thresholds and moderation policies depending on the type and severity of content.

Text moderation models can identify explicit abuse, indirect threats, coded language, and evasive phrasing. They can also account for misspellings, leetspeak, repeated characters, and character substitutions used to bypass simple filters, helping teams catch violations in fast-moving chat and player conversations.

Together, these signals can help teams make more informed decisions about when content should be allowed, reviewed, or acted on.

In-game communication can be used for scams and phishing

The same chat and forum features players use to communicate can also be used for phishing, scams, external promotions, and off-platform transactions. In some cases, the intent behind an interaction only becomes clear after several messages.

Text moderation models can support teams with pinpointing promotions, solicitations, spam, and other policy-violating language within individual messages. When teams need more context, multimodal language models can analyze conversations, forum threads, and in-game interactions to understand how messages relate to one another.

This can help trust & safety teams identify violations that may be difficult to catch by evaluating each message on its own.

Building communities players want to come back to

The way players interact with one another has become an important part of the overall video games experience. That raises the standard for how platforms manage the communities that form around their games. Creating spaces where players want to participate means giving them room to connect while maintaining clear expectations for how those communities are used.

Hive helps gaming companies keep in-game interactions safe and enjoyable, understand nuanced player interactions, verify player authenticity, detect phishing and external promotions, and support game asset creation. Our enterprise-grade AI models are designed to support content moderation across visual content, analyze conversations and forum threads, identify AI-generated profiles, detect messages promoting external links or game-item sales, and generate image and video assets. Contact us today to learn more.