Social Network Relationship Evaluation via Shared Content Scoring
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Solution Overview
Problem
Current social networking services lack an effective method to determine how information flows between social networking profiles, especially when profiles are not directly connected, making it difficult to analyze and understand the propagation of posts across different platforms.
Innovation Solution
A network-based computing technology that evaluates relationships between social networking profiles by analyzing shared content, using a server to monitor and score connections based on a formula that considers shared data and inconsistencies, allowing for action to be taken based on these evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If social networking services only track direct connections between profiles, then the system complexity remains low, but the ability to analyze information flow between indirectly connected profiles is lost
Solution Approach 1:
The patent introduces an intermediary evaluation system that acts as a mediator between social networking services and third-party analyzers. This intermediary component collects profile data, executes evaluation formulas, and returns relationship scores without requiring direct integration between all profiles, thus enabling indirect connection analysis while managing system complexity
Solution Approach 2:
The relationship evaluation system is segmented into independent modules: data collection components, formula execution engines, and scoring mechanisms. This segmentation allows the system to handle complex relationship analysis by breaking it down into manageable operations that can be executed independently for different profile pairs
2Measurement precision
If the system monitors all social networking profiles continuously, then the measurement precision of relationship evaluation is improved, but the loss of time for data collection increases
Solution Approach 1:
Instead of continuously monitoring all profiles, the system implements partial monitoring by selectively sampling profile data at strategic intervals. The evaluation formula can process multiple profiles in parallel, and the system can adjust the sampling frequency based on the dynamic nature of social networks, achieving sufficient measurement precision without excessive time loss
3Reliability
If the evaluation formula considers multiple factors including shared content and inconsistencies, then the reliability of relationship scoring is improved, but the device complexity for processing increases
Solution Approach 1:
The evaluation formula uses parameter changes by adjusting the weightings of different factors (shared content, inconsistencies, temporal patterns) based on the specific analysis requirements. The system can modify these parameters dynamically to optimize the balance between reliability and processing complexity for different use cases
Data Source
AI summary
This disclosure discloses a network-based computing technology to evaluate relationships between social networking profiles and then to take an action based on such evaluation. This network-based computing technology may include a running logic, whether hardware or software, such as an engine, which may be modularized, that is programmed to score the relationships based on shared content.