Relationship Strength Visualization for Child Safety Monitoring
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Solution Overview
Problem
Parents and guardians face difficulties in monitoring the social interactions of children in the virtual digital world, as these activities are often private and hard to understand, making it challenging to determine the health and safety of their relationships.
Innovation Solution
A computer-implemented method and system that determines and displays relationship strength between a monitored user, such as a child, and their peers based on communication frequency, content, proximity, and location, providing insights into friendships, frenemies, bullying, and other relationships through a user-friendly interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If private communication activities are allowed for children, then social interaction freedom is improved, but monitoring capability deteriorates
Solution Approach 1:
The patent introduces a monitoring system that acts as an intermediary between the child's private communications and the parent's monitoring needs. The system captures communication metadata (frequency, duration, contacts) without invading privacy, translating private activities into visible relationship indicators that parents can observe without direct access to communication content.
Solution Approach 2:
The system creates a simplified copy or representation of the child's social relationships through visual indicators and relationship strength metrics. Instead of monitoring actual communication content, the system generates a副本 showing relationship patterns, contact frequency, and social network structure that parents can review.
2Measurement precision
If communication frequency is tracked to determine relationship strength, then monitoring accuracy is improved, but user privacy is worsened
Solution Approach 1:
The patent extracts only the necessary metadata from communications (frequency, duration, contact identity) while leaving the actual communication content private and inaccessible. This selective extraction provides sufficient information for relationship analysis without compromising the privacy of the actual conversations.
Solution Approach 2:
The system applies different levels of monitoring to different aspects of communication: metadata (frequency, duration) is fully monitored for relationship analysis, while communication content remains private. This local differentiation allows precise relationship measurement without uniform privacy invasion.
Data Source
AI summary
A computer-implemented method of displaying indications of relationships of device users is provided. The method includes determining relationship strength between a first user and at least one other user wherein the relationship strength is determined based on a frequency of communication between the first user and the at least one other user. A first indication corresponding to the first user is displayed on a display of a device, and at least one other indication corresponding to the at least one other user is displayed on the display, wherein the at least one other indication is shown distanced from the first indication based on the determined relationship strength. A system for performing the method is further provided.