Social Graph Content Targeting via Friend Network Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing social networks face challenges in effectively targeting content to users based on their relationships, as current methods often require explicit user specification and may not reach interested individuals, leading to inefficient advertising and limited product/service promotion.
Innovation Solution
A system and method that generates a data structure linking users based on social relationships derived from electronic documents, allowing content to be targeted to unspecified acquaintances by selecting nodes in a social graph that neighbor the content originator, enabling efficient distribution of announcements and advertisements to appropriate audiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If content is distributed to a large group of members, then the reach of the content increases, but the precision of targeting interested users decreases
Solution Approach 1:
The system segments the user base into connected groups based on social relationships (friend graphs) extracted from electronic documents. Instead of treating all users as a single audience, the patent divides the network into meaningful segments where users are grouped by their social connections to the content originator, enabling precise targeting within relevant segments while maintaining scalability to large audiences.
Solution Approach 2:
The patent introduces social relationship data (friend graphs) as an intermediary layer between content and users. This intermediary structure enables indirect targeting by identifying users who are connected to the content originator through social ties, even when those users are not explicitly specified in the distribution request, thus bridging the gap between broad reach and precise targeting.
2Measurement precision
If explicit user specification is required for content distribution, then the precision of targeting increases, but the ease of operation decreases
Solution Approach 1:
The system performs automatic friend graph extraction and analysis without requiring user intervention. The patent automatically identifies connected users based on social relationships embedded in electronic documents, eliminating the need for users to manually specify recipient lists while maintaining high targeting precision through relationship-based identification.
Solution Approach 2:
The system pre-extracts and stores social relationship data (friend graphs) from electronic documents before content distribution is needed. This preliminary action creates a ready-to-use mapping of user connections that enables rapid, precise targeting when content distribution requests are made, without requiring real-time analysis or user input.
3Area of stationary object
If traditional advertising methods are used, then the coverage area increases, but the relevance to interested audiences decreases
Solution Approach 1:
The patent applies local quality by tailoring content distribution to specific social contexts rather than using uniform advertising approaches. Users who are connected to the content originator through social relationships receive different treatment than unconnected users, with the system prioritizing distribution to locally relevant audiences based on their social proximity to the content source.
Solution Approach 2:
The system changes the targeting parameter from random or demographic-based selection to relationship-based selection. By using the friend graph structure derived from electronic documents, the patent transforms how audiences are identified, shifting from broad coverage parameters to relationship-strength parameters that better predict user interest and engagement.
Data Source
AI summary
The subject matter of this specification can be embodied in, among other things, a method that includes generating a data structure that links users based on social relationships and permits a first user to target content to other users that are linked to the first user via a social relationship.