Social Network Analysis for Personalized Content Previews
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Solution Overview
Problem
Existing content preview systems fail to provide personalized and relevant previews to individual users based on their social network relationships, as the interesting portions identified by one person may not be interesting to another, leading to suboptimal content acquisition decisions.
Innovation Solution
A system and method that generate digital content previews by analyzing social network relationships and identifying interesting portions of digital content items based on input signals from multiple users within a content distribution server, tailoring previews for each user within their respective social networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content previews are generated based on general content analysis, then the preview generation process is simple, but the preview is not personalized and may not be interesting to the specific user
Solution Approach 1:
The patent introduces a social network analyzer as an intermediary component that mediates between the content analyzer and the preview generator. This intermediary processes social network data and integrates it with content analysis results to generate personalized previews, thereby achieving personalization without requiring complete redesign of the entire system architecture
Solution Approach 2:
The system segments the preview generation process into distinct functional modules: content analysis module, social network analysis module, and preview generation module. Each module handles specific tasks independently, with the social network analysis module processing user relationship data separately from content processing, then combining results in the preview generation stage
2Reliability
If content previews are tailored to individual users based on social network analysis, then user engagement and informed decision-making improve, but the system complexity and processing requirements increase
Solution Approach 1:
The social network analyzer is designed as a multi-functional component that performs multiple tasks: analyzing user relationships, identifying influential users, determining social clusters, and integrating this information with content analysis. This universal approach handles various personalization needs through a single integrated system rather than requiring separate specialized components
3Adaptability or versatility
If the system analyzes social network relationships to generate personalized previews, then the preview becomes more relevant to the user, but the time required for analysis and preview generation increases
Solution Approach 1:
The system performs preliminary analysis of social network structures and user relationships in advance, building and maintaining social network models before actual preview generation is needed. This pre-processing of social graph data allows the system to quickly query and retrieve relevant social information during preview generation without performing complex analysis in real-time
Solution Approach 2:
The system applies partial social network analysis by focusing only on the most relevant social connections and relationships for each user rather than analyzing the entire social network. It selectively processes social data based on user-specific criteria such as close friends, family members, or highly influential contacts, reducing the scope of analysis while maintaining personalization effectiveness
Data Source
AI summary
Disclosed is a system and method for generating a preview of a digital content item using social network analysis. Members of a social network who acquire the digital content item may identify interesting portions of the digital content. When a member of the social network requests a preview of the digital content item, typically in anticipation of an acquisition of the digital content item, the interesting portions of the digital content item identified by fellow social network members are considered in the generation of the preview. Selection of the interesting content for preview may include more identified content, as well as social network relationship and role magnitudes. The digital content item may include: text, such as books or articles; multimedia such as audio/video; and interactive, such as games or virtual worlds.