Granular Privacy Control in Social Networks via Association Segmentation
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Solution Overview
Problem
Conventional social networking websites lack granular control over individual pieces of information privacy, leading to viral distribution of information without regard for privacy, primarily focusing on social relationships rather than associations, which is inadequate for entities like corporations or organizations.
Innovation Solution
A system and method that recognizes associations between entities separately from social relationships, allowing for granular privacy control over individual pieces of information, enabling entities to manage and distribute information appropriately within their networks, using modules such as an entity profile module, association module, achievement module, and ratings module to set privacy levels for achievements, certificates, and messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional social networking websites recognize only social relationships, then the system is simple to operate, but privacy control over individual information is insufficient
Solution Approach 1:
The patent segments privacy control into multiple dimensions by introducing both social relationship recognition and association recognition as separate mechanisms. This allows the system to maintain operational simplicity for social networking while adding granular privacy control through associations, resolving the contradiction between ease of operation and privacy control.
Solution Approach 2:
The patent adds a new dimension to the social networking system by introducing association recognition alongside existing social relationship recognition. This dimensional expansion enables fine-grained privacy control over individual information without complicating the basic social networking functionality, thus resolving the contradiction.
2Device complexity
If privacy controls are applied only in the context of social relationships, then the system structure remains simple, but granular control over individual pieces of information is not achieved
Solution Approach 1:
The patent segments the privacy control mechanism into separate modules: social relationship recognition module and association recognition module. This segmentation allows the system to maintain relatively simple overall structure while achieving granular privacy control through the association module, resolving the contradiction between system simplicity and control precision.
Solution Approach 2:
The patent introduces association recognition as an intermediary mechanism between the basic social relationship framework and the need for granular privacy control. This intermediary layer provides fine-grained control over individual information without fundamentally complicating the core social networking structure.
3Productivity
If information is distributed in a viral manner across the network, then information reach is maximized, but privacy of the information is compromised
Solution Approach 1:
The patent introduces dynamic privacy control mechanisms that allow information distribution characteristics to change based on association levels. Instead of fixed viral distribution, the system dynamically adjusts information reach according to the association between entities, resolving the contradiction between distribution efficiency and privacy protection.
Solution Approach 2:
The patent applies local quality control by enabling different privacy settings for different pieces of information based on their association context. This allows certain information to maintain viral distribution while other sensitive information remains restricted, resolving the contradiction between overall distribution efficiency and individual privacy protection.
Data Source
AI summary
A system and method for hosting a social network that enables entities to particularly manage the privacy level of content posted on the social network. This may enable an entity to distribute news, congratulations, accolades, invitations, and/or other internal information within the social network to members, employees, students, investors, and/or other parties.