Content Flag Analysis System for Prioritizing Review
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Solution Overview
Problem
The rapid pace of online content creation and sharing overwhelms content hosting services, making comprehensive review impractical, and reliance on untrained users for flagging potentially inappropriate content leads to inaccuracies and abuse, complicating the monitoring of Terms of Use and legal violations.
Innovation Solution
A system that includes a reception component for flag information, an analyzer component to determine the accuracy of flags, and a categorization component that performs a cost/benefit analysis to prioritize administrative actions, utilizing a trained classifier to efficiently manage and allocate resources for reviewing flagged content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user flagging systems are used to identify potentially inappropriate content, then the service can leverage community size to draw attention to violations, but the judgment of untrained users creates inaccuracies and abuse
Solution Approach 1:
The patent introduces an intermediary analysis system that sits between user flags and administrative review. This system analyzes multiple flags, user histories, and content patterns to determine whether flagged content actually requires review, filtering out inaccurate flags before they reach human reviewers.
Solution Approach 2:
The system implements feedback loops where administrative review outcomes feed back into the analysis system, improving its ability to distinguish accurate from inaccurate flags. User flagging behavior is also monitored and fed back to adjust flagging thresholds and user trust scores.
2Reliability
If comprehensive review of all content submissions is attempted, then content appropriateness can be ensured, but the pace of content creation overwhelms review capacity
Solution Approach 1:
Instead of reviewing all content or all flags, the system performs partial action by selectively reviewing only those flags that pass through the analysis system and meet certain confidence thresholds. This partial review approach maintains reliability for high-risk content while preserving productivity by skipping low-risk items.
Solution Approach 2:
The analysis system performs preliminary filtering of flags before they reach human reviewers, pre-processing the content to identify which flags warrant further review. This preliminary action reduces the burden on human reviewers while maintaining oversight of potentially inappropriate content.
3Measurement precision
If human review of flagged content is performed, then accurate identification of violations can be achieved, but the volume of flagged content makes this difficult even for large services
Solution Approach 1:
The system performs preliminary analysis of flags using automated techniques before human review, preparing summaries and confidence scores that help reviewers quickly assess each flag. This preliminary action reduces the time required for human review while maintaining accuracy.
Solution Approach 2:
Human reviewers focus only on flags that pass through the analysis system and meet certain criteria, rather than reviewing all flagged content. This partial review approach maintains high accuracy for problematic content while reducing overall review time and resource requirements.
Data Source
AI summary
This disclosure relates to screening potentially inappropriate online content. A flag is received that indicates online content is potentially inappropriate. The flag is generated by a source, such as a user, or a content classifier. The potential accuracy of the flag is determined or inferred based on a variety of factors, including a reputation of the source, and the flag is categorized as requiring higher priority administrative action or requiring lower priority administrative action based in part on the potential accuracy of the flag. In addition, administrative action is taken based in part on the categorization of the flag.