User Content Ranking via Freshness and Reputation Metrics
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Solution Overview
Problem
Existing methods for displaying user-generated content on platforms like Yahoo! face challenges in balancing quality and freshness, leading to issues such as spam, low-quality posts, and adverse effects on user experience and search engine rankings, particularly due to the default chronological view or community rating-based sorting methods.
Innovation Solution
A method that calculates a rank for user-generated content based on freshness and reputation metrics, using parameters like user ratings, engagement, and time of submission, with adjustable weights to prioritize either freshness or reputation, ensuring high-quality content remains visible while allowing newer content to gain visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If chronological sorting (newest first) is used to show fresh content, then content freshness is improved, but comment quality deteriorates due to spam and low-quality posts
Solution Approach 1:
The patent changes the sorting parameter from simple chronological order to a composite ranking score that incorporates multiple factors including freshness weight, reputation weight, and engagement metrics. This allows the system to balance between showing fresh content and maintaining quality by adjusting the weights of different parameters in the ranking calculation.
2Reliability
If community rating sorting is used to show high-quality content, then comment quality is improved, but first mover advantage and irrelevance to current story occur
Solution Approach 1:
The patent implements a dynamic ranking system where the importance of different factors (freshness vs. reputation) can be adjusted through weights. The ranking is not static but adapts based on configurable parameters, allowing the system to balance between showing established high-quality comments and newer relevant comments from the current story.
3Productivity
If reverse chronological sorting is used to balance freshness and quality, then user engagement increases, but spam and troll content increases severely
Solution Approach 1:
The patent applies preliminary filtering and ranking before content is displayed. By pre-calculating a composite ranking score that factors in reputation, engagement metrics, and freshness, the system filters out low-quality content (spam, trolls) before it reaches the user, while still maintaining high engagement by showing relevant fresh content.
4Reliability
If complex off-line batch jobs are used to compute popular comments, then comment quality is improved, but performance overhead increases
Solution Approach 1:
The patent implements a self-service ranking system where the ranking score is automatically calculated and updated based on real-time data from reputation metrics, engagement metrics, and freshness calculations. The system serves itself by continuously updating rankings without requiring complex off-line batch jobs, reducing performance overhead while maintaining quality.
Data Source
AI summary
Ordering user generated content includes: calculating a rank of the user generated content associated with an on-line property, the calculating based on a calculated freshness score and reputation metrics; storing the calculated rank as an indexed field; receiving a request to serve the on-line property; at run-time, sorting the user generated content by rank using the indexed field; and presenting the sorted user generated content along with the requested on-line property.