Content Section Scoring and Visualization for Social Media
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Solution Overview
Problem
Users face stress and anxiety due to the overwhelming amount of content on social networking systems, as they struggle to identify valuable information amidst a vast amount of irrelevant content, requiring significant time to manually sort through it.
Innovation Solution
A system that divides content items into sections, determines scores for each section based on user comments, and applies visualization techniques to highlight valuable sections, allowing users to quickly identify important information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually sort through all available content to identify valuable information, then information completeness is improved, but time consumption increases significantly
Solution Approach 1:
The patent segments content items into multiple sections (e.g., headline, body, comments) and calculates separate importance scores for each section based on user engagement metrics. This allows the system to identify and highlight only the valuable portions of content rather than requiring users to read everything, thus reducing time consumption while maintaining information completeness.
Solution Approach 2:
The patent replaces the mechanical manual sorting process with an automated computational system that uses machine learning models and engagement metrics to automatically score and rank content sections. This substitution eliminates the need for users to manually evaluate each piece of content, dramatically reducing time consumption while preserving access to valuable information.
2Loss of information
If users read all available content to avoid missing important information, then information completeness is improved, but user stress and anxiety increase
Solution Approach 1:
The patent extracts and highlights only the most valuable sections of content based on importance scores derived from user engagement metrics. By presenting only the essential portions of content and allowing users to skip lower-scoring sections, the system reduces the cognitive burden and stress associated with reviewing overwhelming amounts of content while ensuring users don't miss important information.
3Loss of information
If the system provides all content without filtering, then information completeness is improved, but ease of operation deteriorates due to overwhelming content volume
Solution Approach 1:
The patent performs preliminary processing of content by calculating importance scores for different sections before presenting them to users. The system pre-analyzes content using engagement metrics and machine learning models to identify valuable sections, then presents this pre-filtered content to users. This preliminary action reduces the operational burden on users while maintaining access to complete information.
Data Source
AI summary
Rendering a content item of a social networking system can include dividing, using a processor, a content item into a plurality of sections, determining, using the processor, a score for each of the plurality of sections, and applying, using the processor, a visualization technique to a selected section of the content item based upon the scores of the plurality of sections.