Social Network Generation from Communication Data
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Solution Overview
Problem
Existing social networking systems fail to incorporate all social connections, as relationships outside user-defined networks remain unlinked due to lack of comprehensive data integration from various communication types.
Innovation Solution
A method and system that determine and group social connection data from communications facilitated by computing devices, generating communications-based social networks and aggregated networks by linking nodes shared between them, using device identifiers and evaluating connection strength based on communication frequency and metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user-defined social networks are used, then the network structure is deliberately established and controlled, but the network completeness is reduced as only a portion of actual linkages are included
Solution Approach 1:
The patent merges multiple data sources including communications data, social network data, and contact list data to create a comprehensive social network. The system combines information from email communications, text messages, calls, and existing social network linkages to generate a unified network graph that reflects actual relationships, thereby improving network completeness while managing data integration complexity through systematic merging of heterogeneous data types.
Solution Approach 2:
The system implements a universal data processing framework that handles multiple communication types (email, text, calls) and data sources through a unified approach. The network generation mechanism works universally across different communication platforms and data formats, extracting social connection data from various sources and integrating them into a single comprehensive network structure that serves multiple analytical purposes.
2Measurement precision
If comprehensive data integration from various communication types is implemented, then the accuracy of social connections is enhanced, but the system complexity increases
Solution Approach 1:
The patent segments the complex data integration process into distinct modules: communications data processing, social network data processing, contact list processing, and network graph generation. Each communication type (email, text, call) is processed separately through standardized pipelines, and results are integrated in a structured manner. This segmentation reduces system complexity by breaking down the monolithic integration task into manageable, independent processing stages.
Solution Approach 2:
The system introduces intermediary processing layers that standardize and normalize data from different communication sources before integration. These intermediaries transform heterogeneous data formats into a unified schema, mediating between diverse input sources and the final network structure. This intermediary approach simplifies the integration process by providing a standardized interface that handles the complexity of multi-source data convergence.
3Loss of information
If user-defined networks are used, then the network structure is deliberately established, but the actual relationships outside the network remain unlinked
Solution Approach 1:
The system performs preliminary data collection and processing by gathering communications data, social network data, and contact list data before network generation. It pre-processes this data to extract potential social connections and relationship indicators, preparing the foundation for automatic network construction. This preliminary action ensures that all relevant relationship information is captured and organized before the actual network generation occurs, reducing information loss.
Solution Approach 2:
The system implements self-service automation where the network generation process autonomously analyzes communications data, identifies social connections, and constructs the network graph without manual intervention. The algorithm automatically determines relationship strength based on communication patterns, selectively invites connections based on detected relationships, and generates the final network structure independently. This automation maintains ease of operation while comprehensively capturing actual relationships.
Data Source
AI summary
Embodiments generally relate to generating social networks from device specific communications. In one embodiment, a method includes determining social connection data included in communications, the communications being associated together via a device identifier and generating a communications-based social network for an end user from the determined social connection data, the end user being associated with the device identifier.