Social Network Content Reach Visualization via Label Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional social networking systems lack the capability to measure the 'virality' of content items and track user interactions effectively, making it difficult for users to understand the reach and impact of their posted content.
Innovation Solution
The system creates label objects and edge objects to track content items and user interactions, allowing users to visualize the reach of their content by retrieving and processing this data to provide metrics such as reach, virality, engagement, and conversion metrics, which are presented in various data graph formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional social networking systems are used, then basic content sharing is enabled, but the capability to measure virality and track user interactions is insufficient
Solution Approach 1:
The patent segments the tracking system into distinct components: label objects attached to individual content items to track their propagation, and edge objects to track user interactions. This segmentation allows precise measurement of content reach without requiring a monolithic complex system, as each component has a specific tracking function.
Solution Approach 2:
The patent introduces label objects as intermediary elements that attach to content items and travel with them through the social networking system. These label objects serve as mediators that carry tracking information without altering the core content sharing functionality, enabling measurement while maintaining system simplicity.
2Measurement precision
If label objects and edge objects are created to track content propagation, then measurement precision is improved, but system complexity increases
Solution Approach 1:
The label objects serve multiple functions: they identify the content item, track its propagation path, record user interactions, and enable reach measurement. This multi-functionality reduces the need for separate tracking mechanisms, thereby improving measurement precision without proportionally increasing system complexity.
Solution Approach 2:
The patent implements a nested data structure where label objects are embedded within content items, and edge objects are associated with user interactions. This nesting allows the tracking data to be organized hierarchically, making it manageable and retrievable without overwhelming system complexity.
3Loss of information
If comprehensive reach data is collected, then information completeness is improved, but data processing time increases
Solution Approach 1:
The patent performs preliminary actions by attaching label objects to content items at the moment of posting and continuously updating them as the content propagates. This preliminary tracking ensures that when reach data is requested, the information is already collected and organized, reducing retrieval time while maintaining completeness.
Solution Approach 2:
The system implements feedback mechanisms where label objects continuously update their state as content propagates through the network. This real-time feedback ensures that reach data is always current and complete without requiring lengthy batch processing operations when data is requested.
Data Source
AI summary
Effects of content communications propagated to users of a social networking system may be tracked and measured by the social networking system. Identifiers of content presented to users within a time period before the users interact with the content are recorded. As users interact with the content, additional data describing the interactions with the content and the users interacting with the content are stored. Various metrics may be determined from the data describing interactions with the content. For example including virality metrics and reach metrics, may be determined and presented to the user that posted the content.