Social Network User Attribute Verification via Peer Feedback
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Solution Overview
Problem
Existing social networking platforms lack effective verification methods for user personal attributes, leading to potential misrepresentation and safety concerns, especially for children, and existing verification methods involving third-party authentication are not economically viable or practical for users.
Innovation Solution
A system and method for verifying user personal attributes by receiving information from users, requesting veracity feedback from other users, assigning confidence scores based on feedback, and publishing these scores to the social network, which can include determining physical location and verifying attributes through interactive voice or video sessions, without relying on trusted agents or personal confidential information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If third-party authentication with personal confidential information is used to verify user attributes, then verification accuracy is improved, but user privacy protection deteriorates and verification costs increase
Solution Approach 1:
The patent extracts the verification function from centralized third-party authentication systems and distributes it to individual users through peer feedback mechanisms. Instead of requiring users to submit personal confidential information to centralized authorities, the system collects verification data from multiple independent users who interact with the target user, thereby eliminating privacy risks associated with centralized storage of sensitive information.
Solution Approach 2:
The system enables users to verify each other's attributes through direct interaction and feedback without requiring external third-party authentication services. Users themselves perform the verification by providing feedback on observed attributes of other users, making the verification process self-service oriented and eliminating the need for users to disclose personal confidential information to external authorities.
2Measurement precision
If third-party authentication with personal confidential information is used to verify user attributes, then verification accuracy is improved, but verification costs increase making it economically unpracticable
Solution Approach 1:
The verification system operates as a self-service mechanism where users contribute verification feedback voluntarily during their normal interactions on the platform. The system leverages existing user behavior and interactions to collect verification data, eliminating the need for expensive dedicated authentication services or manual verification processes.
Solution Approach 2:
The system implements continuous feedback loops where users provide verification feedback on observed attributes of other users during platform interactions. This feedback is aggregated to generate confidence scores that improve over time as more verification data is collected, creating a self-reinforcing verification ecosystem that becomes more accurate without requiring additional external verification resources.
3Ease of operation
If no verification system is implemented, then user privacy is protected and platform accessibility is maintained, but reliability of user attributes deteriorates enabling false portrayals
Solution Approach 1:
The patent introduces confidence scores as an intermediary metric that bridges the gap between maintaining platform accessibility and ensuring attribute reliability. These confidence scores are calculated from aggregated peer feedback and serve as a mediator that allows users to assess the reliability of other users' attribute claims without requiring mandatory verification that would hinder platform accessibility or compromise privacy.
Solution Approach 2:
The system changes the parameter of verification from binary (verified/not verified) to a continuous confidence score that reflects the degree of reliability. This parameter change allows for nuanced assessment of user attributes, enabling the platform to maintain high accessibility while providing users with information about attribute reliability through the confidence score metric.
Data Source
AI summary
A computer host is configured to perform a method for defining user attributes with associated verification values for social networking accounts. The attributes concern the user's personal characteristics or attributes. The host publishes the attribute information to other clients together with interactive objects for soliciting corroboration of the attribute information. The host receives feedback information from other account holders, such as survey response data, concerning the veracity of the attribute information. The host processes the evaluation information and the feedback information to provide a veracity score of each attribute reported for each account holder, or for collections of attributes, by weighing the evaluation information and feedback information by a computed reliability factor for each source from which processed information is obtained.