Social Network User Relationship Analysis via Thread Segmentation
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Solution Overview
Problem
Current social networking services fail to accurately analyze and represent the complex relationships among users, particularly overlooking the interactions between those who write original texts and those who comment, resulting in limited understanding of user intimacy and social connections.
Innovation Solution
A method and server system that analyze and categorize users based on their interactions by dividing text and comment threads according to preset criteria, determining intimacy levels using factors like frequency, length, time interval, and semantic analysis, and providing selective access and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional social networking services analyze user relationships based on unilateral connections only, then the analysis process is simple, but the accuracy of understanding user intimacy and social connections is insufficient
Solution Approach 1:
The patent segments user relationships into multiple dimensional categories including original text relationships, comment relationships, and reply relationships. By dividing the complex relationship analysis into these distinct segments, the system can accurately capture unilateral and bilateral interactions separately, thereby improving measurement precision without overwhelming system complexity
Solution Approach 2:
The patent introduces multiple analytical dimensions beyond simple unilateral connections, including comment threads, reply chains, and intimacy levels. This dimensional expansion allows the system to comprehensively analyze both unilateral and bilateral relationships, significantly improving the accuracy of user relationship understanding while maintaining manageable complexity through structured dimensionality
2Loss of information
If the system divides texts and comments into multiple threads for analysis, then the understanding of user relationships is more comprehensive, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-dividing texts and comments into organized threads based on clear criteria (original texts, comments, replies) before analysis. This pre-structuring of data into manageable threads reduces the computational burden during actual analysis, maintaining information completeness while reducing processing time through advance organization
Solution Approach 2:
By segmenting the content into distinct threads (original text threads, comment threads, reply threads), the system processes information in smaller, manageable units rather than analyzing all content simultaneously. This segmentation preserves complete relationship information while significantly reducing the time and computational resources required for analysis
3Measurement precision
If the system categorizes users based on multiple factors including frequency, length, time interval, and semantics, then the intimacy level assessment is more accurate, but the computational complexity increases
Solution Approach 1:
The patent segments the intimacy assessment into distinct analytical factors: frequency of interaction, length of texts, time intervals, and semantic content. Each factor is analyzed separately and then integrated to form a comprehensive intimacy level assessment. This segmentation improves measurement precision by considering multiple dimensions while managing algorithmic complexity through structured factor-based analysis
Solution Approach 2:
The patent introduces multiple assessment dimensions for intimacy levels, moving beyond simple interaction counting to include temporal dimensions (time intervals), quantitative dimensions (frequency, length), and qualitative dimensions (semantics). This multi-dimensional approach significantly improves assessment accuracy while maintaining manageable complexity through organized dimensional analysis
Data Source
AI summary
A method for providing a social networking service (SNS) preferably includes receiving an input of an original text and a comment on the original text according to execution of a SNS program, dividing the original text and the comment into a plurality of threads according to a preset criterion, analyzing relationships between users who write the original text and/or the comment included in the plurality of threads, and categorizing the users according to a result of the analysis.