Member Value Scoring in Social Networks
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Solution Overview
Problem
Social networks lack effective mechanisms to measure and characterize the value provided to their members, hindering the improvement of user engagement and business activities within these platforms.
Innovation Solution
A system that aggregates data from user interactions and activities on online professional networks to calculate scores representing member value through specific value propositions, using an analysis apparatus to compute and display these scores, facilitating the identification of trends and events, and enhancing user understanding and management of network value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If social networks track and maintain data on user interactions and activities, then the ability to measure member value is improved, but the complexity of the system increases
Solution Approach 1:
The patent segments member value measurement into multiple distinct scores, each representing different value propositions (e.g., networking value, business value, engagement value). This allows the complex task of measuring overall member value to be divided into manageable, independently calculable components that can be tracked and analyzed separately.
Solution Approach 2:
The patent introduces an intermediary scoring system that translates raw interaction data into meaningful value metrics. Rather than directly analyzing complex interaction patterns, the system uses intermediate score representations that bridge the gap between raw data and actionable insights, simplifying the measurement process.
2Loss of information
If the system calculates multiple scores for different value propositions, then the characterization of member value is improved, but the computational resources required increase
Solution Approach 1:
By segmenting value measurement into distinct scored value propositions, the system can process and analyze different aspects of member value independently. This allows computational resources to be allocated efficiently to specific value propositions based on their importance and the available data, rather than requiring all resources for a single comprehensive analysis.
Solution Approach 2:
The system calculates scores for specific value propositions based on relevant data availability and business needs, rather than computing all possible metrics for all members. This partial action approach ensures that computational resources are focused on the most critical measurements while still providing comprehensive value characterization where data exists.
3Measurement precision
If the system aggregates data from multiple sources to calculate member value scores, then the accuracy of value measurement is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments data aggregation by value proposition, collecting and processing data relevant to each specific score separately. This segmentation makes the aggregation process more manageable by focusing on specific data types and sources for each value proposition rather than attempting to aggregate all data simultaneously.
Solution Approach 2:
The scoring system acts as an intermediary layer between raw interaction data and value measurement. This intermediary structure standardizes how data from multiple sources is collected, processed, and combined for each value proposition, reducing the complexity of data aggregation while maintaining measurement accuracy.
Data Source
AI summary
The disclosed embodiments provide a system for processing data. During operation, the system obtains a count of actions associated with a member of a social network, wherein the count comprises a set of action types and a number of actions associated with the member for each of the action types. Next, the system uses the count to calculate a set of scores for measuring the value of the social network to the member, wherein the set of scores is associated with researching and contacting people, building a network, keeping up with connections, staying informed and building knowledge, establishing and managing a reputation, and getting hired. The system then outputs the scores for use in characterizing and improving the value of the social network for the member.