Social Network Connection Suggestion Using Friendship Value
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing social networking systems lack effective mechanisms to suggest meaningful and valuable connections to users, often favoring users with many connections over those with few, and fail to consider the value of suggested connections to the platform's engagement.
Innovation Solution
A system that computes a friendship value between users and potential candidates based on their engagement levels and probabilities of forming connections, using a combination of engines to generate sending and receiving scores and rank candidates, providing suggestions only when the value exceeds a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If existing social networking systems provide connection suggestions based on simple matching algorithms, then the system complexity is low, but the quality and value of suggested connections deteriorates
Solution Approach 1:
The patent transforms the connection suggestion system from simple matching to a multi-parameter evaluation model that considers friendship value, engagement metrics, and connection probability. This parameter-based approach enables precise assessment of connection quality without requiring complex system architecture, as the complexity is managed through mathematical modeling rather than system structure.
Solution Approach 2:
The patent replaces mechanical matching algorithms with a computational value assessment system that uses friendship value calculations, engagement metrics, and probability models. This substitution allows the system to evaluate connection quality precisely through computational methods rather than simple rule-based mechanics.
2Quantity of substance
If the system provides connection suggestions to all users equally, then user coverage is maximized, but the value to users with many connections deteriorates compared to users with few connections
Solution Approach 1:
The patent applies local quality by providing differentiated connection suggestions based on individual user characteristics. Instead of uniform treatment, the system calculates personalized friendship values and engagement metrics for each user, ensuring that connection suggestions are tailored to their specific needs and potential value to the platform.
Solution Approach 2:
The system dynamically adjusts connection suggestions based on real-time engagement metrics and friendship value calculations. The value of a connection suggestion changes dynamically based on user activity levels, connection patterns, and platform engagement, allowing the system to optimize recommendations for each user's current state rather than using static criteria.
3Measurement precision
If the system calculates detailed friendship value and engagement metrics for each connection suggestion, then connection quality improves, but computational complexity and processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing engagement metrics, friendship values, and connection probabilities in databases. These pre-computed values are readily available when generating connection suggestions, eliminating the need for real-time complex calculations and reducing processing time while maintaining high measurement precision.
Solution Approach 2:
The system creates simplified copies of complex engagement metrics and friendship values that can be quickly retrieved and used for connection suggestions. Instead of performing full computational analysis for each suggestion, the system uses pre-computed proxy values that capture the essential information needed for accurate assessment without the computational overhead.
Data Source
AI summary
Techniques introduced here include a system and method for determining whether to provide a user of a social networking system with candidate users (i.e., potential contacts) with whom the user does not already have any connections with. In some embodiments, the system generates a set of candidate users based on a value (e.g., to the social networking system) associated with each potential connection formed between the user and the set of candidate users. In one or more embodiments, the system ranks the candidate users based on their connection-value to the social networking system and provides the ranked candidate users as suggested new connections to the user.