Social Network Supply Demand Calculation for Study Fields
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Solution Overview
Problem
Students often select a field of study without considering its employability, as they lack information about the field's job market prospects, including supply and demand, leading to varying employment rates and salary ranges.
Innovation Solution
A social network system calculates the supply and demand for specific fields of study based on member and company data, providing students with a competition value and dispersion value to inform their choices through recommendations and alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If students select a field of study without information about employability, then students can freely choose their field of study, but employment rates and salary ranges vary significantly
Solution Approach 1:
The system collects data on employment rates, salary ranges, and job demand for different fields of study, then feeds this information back to students through the social network platform. This feedback loop enables students to make informed decisions while maintaining their freedom of choice, resolving the contradiction between selection freedom and employment reliability.
Solution Approach 2:
The patent introduces an intermediary information system that mediates between the labor market (employers, job data) and students. This intermediary processes and presents employability information in an accessible format, allowing students to make better-informed choices without restricting their freedom of selection.
2Loss of information
If the social network system calculates and provides supply and demand information for fields of study, then students can make informed decisions, but the system complexity increases
Solution Approach 1:
The patent leverages the existing social network platform's infrastructure (user profiles, data storage, communication channels) to deliver employability information. By making the social network system multi-functional - serving both its original social purposes and the new career guidance function - the patent avoids building a completely separate complex system while still providing comprehensive information.
Solution Approach 2:
The system automatically collects, processes, and presents supply and demand information using algorithms that analyze existing data in the social network. This self-service approach minimizes manual intervention and complex operational structures, reducing system complexity while maintaining comprehensive information availability.
Data Source
AI summary
Techniques for presenting a recommendation to a member of a social network in a specific field of study are described. A predictor can access, from a database in the social network, educational data of a plurality of students and post-graduate data of a plurality of graduates in the social network. Additionally, the predictor can determine a subset of students associated with a specific field of study, and can calculate a demand for the specific field of study based on the accessed data. A recommendation generator can calculate a competition value for the specific field of study based on the determined subset of students and the calculated demand for the specific field of study. Subsequently, the recommendation generator can cause a presentation, on a display of a device, of a recommendation associated with the specific field of study, the recommendation being based on the calculated competition value.