Distributed Annotation Moderation via Selective User Subsets
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Solution Overview
Problem
Conventional systems fail to effectively moderate annotations in real-time during live content streams, as automated algorithms struggle to prevent irrelevant or abusive comments, and user self-moderation is inefficient due to the high volume of annotations, leading to inappropriate content being distributed to users before it can be tagged and suppressed.
Innovation Solution
A content management system that selectively distributes annotations to subsets of users for initial moderation, allowing users to tag inappropriate or irrelevant comments before they are shared with a larger audience, and prioritizes highly-rated or relevant annotations for wider distribution, using a dynamic display interface to emphasize moderation information and reduce irrelevant content visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated moderation algorithms are used to filter annotations in real-time, then inappropriate content can be blocked, but the algorithms struggle to effectively prevent irrelevant or abusive comments due to high volume and complexity
Solution Approach 1:
The patent introduces a dual-layer moderation system where automated algorithms serve as an intermediary filter before content reaches users. The system uses automated filtering as a first layer of moderation, then introduces a second layer of user-based moderation through selective distribution to moderation queues. This intermediary approach allows the system to handle high volumes of annotations while maintaining effectiveness, as the automated filter reduces the burden on both the system and users.
2Reliability
If user self-moderation is implemented to tag inappropriate comments, then relevant annotations can be identified, but the high volume of annotations makes self-moderation inefficient and slow
Solution Approach 1:
The patent segments the annotation stream into different distribution groups based on various criteria such as user preferences, annotation characteristics, and timing. By dividing the high-volume annotation flow into manageable segments, users are presented with a smaller, more focused set of annotations to moderate. This segmentation dramatically improves moderation speed and efficiency while maintaining content quality, as users can process their assigned segments quickly without being overwhelmed by the total volume.
3Productivity
If all annotations are distributed to all users simultaneously, then user engagement is maximized, but inappropriate or irrelevant content spreads quickly before moderation can occur
Solution Approach 1:
The patent implements preliminary moderation actions before full distribution by creating moderation queues and selectively distributing annotations to subsets of users first. Annotations are distributed to moderation queues where they can be reviewed and tagged by users before being potentially distributed more broadly. This preliminary action ensures that inappropriate content is identified and suppressed before it can spread widely, while still allowing rapid distribution of appropriate content through parallel processing of multiple annotation streams.
4Object-affected harmful factors
If moderation queues are used to filter annotations before distribution, then inappropriate content is reduced, but the time delay before content reaches users increases
Solution Approach 1:
The patent employs periodic distribution cycles where annotations are systematically moved through moderation queues at scheduled intervals rather than requiring individual review before each distribution. The system processes annotations in batches through multiple distribution groups, with each group receiving a subset of moderated content at different times. This periodic action maintains continuous flow of appropriate content while providing regular moderation checkpoints, reducing overall delay compared to sequential review of each annotation.
Data Source
AI summary
Features are provided for the distributed moderation of content annotations and the dynamic display of the moderated annotations. The annotations can be selectively distributed to subsets of user devices currently viewing a content item, thereby limiting the number of annotations that each user device receives. By selectively distributing only subsets of new annotations, users can give more attention to individual annotations and provide meaningful moderation information (e.g., ratings, “likes,” responses, etc.) regarding individual annotations. The annotations can be displayed in a manner that emphasizes the more highly-rated annotations and/or commonly-submitted annotations over other annotations. The annotations can also be displayed in a manner that provides visual cues regarding the sources of individual annotations.