Social Graph Pathfinder for Contextual Messaging
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Solution Overview
Problem
Existing electronic messaging applications lack the ability to effectively utilize social graphs to provide contextual information about connection paths between message senders and recipients, leading to reduced relevance and engagement in messages.
Innovation Solution
Implementing a pathfinder module that analyzes a social graph including nodes representing individuals, companies, and educational institutions to identify and visually present the strongest connection paths between message senders and recipients, allowing for personalized and contextual messaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If electronic messaging applications use traditional messaging methods without social graph integration, then the system complexity remains low, but the message relevance and user engagement decrease
Solution Approach 1:
The patent introduces a social graph as an intermediary data structure that mediates between the messaging system and user relationships. The social graph contains nodes representing users and edges representing relationships, allowing the system to query contextual information (connection paths) without fundamentally redesigning the core messaging infrastructure. This intermediary layer provides contextual information while keeping the overall system architecture manageable.
Solution Approach 2:
The social graph is built and maintained in advance before messaging occurs. User relationships and connection paths are pre-computed and stored in the social graph structure, so when a message is sent, the system can quickly retrieve relevant contextual information without performing complex real-time analysis. This preliminary preparation reduces the computational burden during actual messaging operations.
2Loss of information
If the system presents detailed connection path information to all users, then message relevance improves, but the information overload and user distraction increase
Solution Approach 1:
The patent applies local quality by providing contextual information selectively rather than uniformly to all users. The system analyzes the specific message context, user preferences, and relationship strength to determine what connection path information is most relevant. Only certain connection paths (e.g., strongest connections or most relevant intermediaries) are presented to the user, while less relevant information is omitted. This localized approach ensures that users receive contextual information where it adds value without being overwhelmed by unnecessary details.
3Loss of information
If the system analyzes deep connection paths in the social graph, then the contextual information becomes more relevant, but the computational time and processing resources increase
Solution Approach 1:
The patent implements partial action by limiting the depth of connection path analysis to a reasonable threshold rather than exploring all possible paths in the social graph. The system identifies connection paths up to a certain number of hops (e.g., 2nd or 3rd degree connections) and stops further exploration beyond that point. This partial analysis provides sufficient contextual information for most messaging scenarios while avoiding the exponential computational complexity that would result from analyzing all possible connection paths. The system balances between providing enough context and maintaining acceptable processing performance.
Data Source
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AI summary
A method comprises receiving information identifying a plurality of message recipients to whom electronic messages are to be communicated; analyzing a social graph to identify a plurality of connection paths, each individual connection path connecting a first entity associated with a message sender with one of the plurality of message recipients, the social graph represented by a graph data structure having nodes representing various entities and edges representing associations between entities, with the first entity and each of the message recipients represented as nodes in the graph data structure, each edge connecting two nodes included in a connection path assigned an edge score representing an estimated strength of connection between two entities represented by the two nodes; and generating a plurality of customized instances of an electronic message by automatically modifying a generic electronic message to include information identifying one or more entities to which the first entity and an individual message recipient are both related, as determined by the analysis of the social graph.