Cross-Platform User Profiling for Gaming Toxicity Detection
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Solution Overview
Problem
The video game industry lacks a mechanism for cross-platform user profiling to detect, report, and respond to gaming toxicity, due to the distributed nature of video game environments and the inability to store and process the vast amount of multimedia data generated.
Innovation Solution
A system that extracts telemetry data from video game environments, uses machine learning models to detect incidents of toxicity, and reconstructs game data for manual review, while creating a cross-platform profile that aggregates incident recommendations across different games and accounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system stores and processes vast amounts of multimedia data from video game environments, then the detection accuracy of toxic behavior improves, but the device complexity and data storage requirements worsen
Solution Approach 1:
The patent extracts only the essential telemetry data from the complete multimedia game environment. Instead of storing and processing all multimedia data (videos, audio, textures, models), the system selectively extracts behavioral telemetry data that is sufficient for toxicity detection, thereby reducing data storage and processing complexity while maintaining detection accuracy
Solution Approach 2:
The system creates simplified copies of game behavior data in the form of structured telemetry data. Rather than working with the original complex multimedia data, the patent generates telemetry data copies that capture essential behavioral patterns for toxicity detection, reducing the complexity of data storage and processing while preserving detection capability
2Reliability
If the system creates a centralized cross-platform user profile, then the ability to detect and respond to gaming toxicity improves, but the difficulty of implementing cross-platform coordination worsens
Solution Approach 1:
The patent implements a universal cross-platform user profile system that functions across multiple game titles and platforms. The profile structure and toxicity detection mechanisms are designed to be platform-agnostic, allowing the same system to operate reliably across different game environments without requiring separate implementations for each platform
Solution Approach 2:
The system introduces a centralized profile management intermediary that coordinates between distributed game platforms. This intermediary layer handles the complexity of cross-platform data aggregation and profile synchronization, shielding individual game platforms from the complexity of direct cross-platform coordination while enabling reliable toxicity detection across platforms
3Measurement precision
If the system processes complete native asset data, then the precision of incident detection improves, but the loss of time for data processing increases
Solution Approach 1:
The system extracts only the necessary behavioral indicators from complete native asset data for toxicity detection. Instead of processing all game data, the patent selectively extracts telemetry data containing relevant behavioral patterns, thereby reducing processing time while maintaining incident detection precision
Solution Approach 2:
The system performs preliminary processing of game data to generate structured telemetry data before incident detection occurs. This preliminary extraction and structuring of behavioral data is done in advance, so that when incident detection is needed, the system works with pre-processed telemetry data rather than raw native asset data, significantly reducing detection processing time
Data Source
AI summary
Methods and systems for cross-platform user profiling based on disparate datasets using machine learning models. Specifically, the methods and systems comprising retrieving a cross-platform profile, wherein the cross-platform profile comprises a profile linked to an account, for a user, that is used across multiple assets. The methods and system may then update a status of the cross-platform profile based on incidents detected using machine learning models. The methods and system may then generate for presentation, in a user interface for the account, the status of cross-platform profile.