Social Network Incentive System for Voluntary Data Sharing
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Solution Overview
Problem
Current social networking services gather member information surreptitiously, lacking voluntary participation and effective incentives for data usage, which hinders targeted marketing and product/service promotion based on shared interests and socioeconomic data.
Innovation Solution
A rewards-based social network system where members provide profiles with personal and shopping data, generating a network profile that determines a relative value for merchants, offering incentives to primary and secondary members for data usage, with optional compensation from third parties for data sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If social networking services gather member information surreptitiously, then they can obtain data without explicit member consent, but this approach lacks voluntary participation and effective incentives for data usage
Solution Approach 1:
The system implements a feedback mechanism where members receive incentives (rewards) based on the value of their data contributions. The incentive amount is determined by analyzing the member profile and network profile to assess the relative value of the social network, creating a closed-loop system where data sharing is rewarded rather than extracted surreptitiously
Solution Approach 2:
The system changes the parameter of member motivation from implicit acceptance to explicit voluntary participation driven by incentives. By dynamically calculating incentive amounts based on data value parameters, the system transforms the data collection approach from surreptitious to transparent and reward-based
2Reliability
If the system provides incentives to members for data usage, then voluntary data sharing increases, but the system complexity increases due to incentive calculation and distribution mechanisms
Solution Approach 1:
The system employs self-service mechanisms where the incentive calculation is automatically performed by the social networking service based on predefined criteria. The server computer automatically analyzes member profiles and network profiles to determine incentive amounts, eliminating the need for manual intervention and simplifying the complexity through automation
Solution Approach 2:
The incentive system serves multiple functions simultaneously: it compensates members for data sharing, motivates voluntary participation, and provides a structured approach to data value assessment. By integrating these functions into a unified system, the complexity is managed more effectively
3Productivity
If the system analyzes member profiles to determine network value, then targeted marketing improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of member profiles and generation of network profiles in advance, before marketing campaigns are launched. By pre-processing and storing the analyzed data, the system reduces real-time processing requirements and enables faster marketing deployment while maintaining effectiveness
Data Source
AI summary
A social network server computer forms a social network including a primary member linked to a plurality of secondary members, each of whom provides a member profile. A network profile is generated based on an analysis of the member profiles. A social network server computer then determines a relative value of the social network with respect to a merchant by analyzing the associated network profile, and offers a merchant incentive to the primary member of the network as a function of the determined relative value. In a second embodiment, a merchant computer associated with a merchant determines a relative value of the social network with respect to a merchant by analyzing the network profile, and offers a merchant incentive to the primary member of the network as a function of the determined relative value. The merchant incentives may be also offered to the secondary members of the associated social network.