User Reputation Assessment for Content Reliability
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Solution Overview
Problem
Conventional keyword-based search algorithms, such as PageRank, TrustRank, Anti-Trust Rank, and XRank, are ineffective for user-created content (UCC) due to the lack of textual information and varying data types in social networks, making it difficult to accurately search and rank high-quality UCCs.
Innovation Solution
A computer-implemented method and system that defines networked associations between users based on social activity information, computes user reputation by analyzing link relations, and assesses content reliability using user reputation and social activity data stored in databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional keyword-based search algorithms (PageRank, TrustRank, etc.) are used to search web content, then the search effectiveness for traditional web documents is improved, but the search accuracy for user-created content (UCC) deteriorates due to lack of textual information and varying data types
Solution Approach 1:
The patent transforms the search algorithm from keyword-based to reputation-based by changing the fundamental parameter used for ranking. Instead of using textual keywords and hyperlink structures, the system uses user reputation scores derived from social activity data (number of friends, content interactions, user profiles) to rank UCCs. This parameter change makes the algorithm adaptable to content types that lack traditional textual search elements.
Solution Approach 2:
The patent introduces user reputation as an intermediary metric that mediates between social activity data and content ranking. The reputation score serves as a bridge that translates diverse social interactions (friendships, content likes, comments) into a single quantitative measure that can be used for content search and ranking, making the system versatile across different UCC types.
2Measurement precision
If the number of workers engaged in rating UCC quality is increased, then the accuracy of content quality assessment is improved, but the operational complexity and cost increase
Solution Approach 1:
The patent implements a self-service mechanism where users automatically generate quality assessment data through their social activities (creating content, friending others, liking content). The system automatically calculates reputation scores based on these user-generated activities without requiring manual intervention from rating workers. This eliminates the need for complex manual rating systems while maintaining assessment accuracy.
Solution Approach 2:
The system uses social activity data as continuous feedback to dynamically update user reputation scores. User interactions (creating content, receiving likes, adding friends) provide ongoing feedback that automatically adjusts reputation measurements, replacing the need for periodic manual quality assessments by workers.
3Reliability
If user reputation is computed based on comprehensive social activity information, then the reliability of reputation assessment is improved, but the computational complexity increases
Solution Approach 1:
The patent segments the computation of user reputation into distinct components based on different types of social activities (number of friends, content creation statistics, interaction data). Each component is calculated separately using simple aggregations, and then combined to form the overall reputation score. This segmentation reduces computational complexity compared to analyzing all social activity data as a single complex problem.
Solution Approach 2:
The system uses a subset of available social activity data (key metrics like friend count, content likes, comments) rather than processing every possible interaction detail. This partial action approach captures sufficient reliability information while avoiding the computational burden of analyzing complete social graphs and all user interactions in depth.
Data Source
AI summary
A method and system for assessing a user reputation and/or a content reliability on contents sharing web sites is provided. In one embodiment, the method includes defining a networked association between users based on social activity information related to the users' social activities on a contents sharing web site, the users' social activities including social activities between the users and/or social activities of the users on the contents sharing web site; obtaining a link relation for at least one of the users based on the networked association; and computing a user reputation for the at least one of the users based on the link relation. The method may further include computing a content reliability of the at least one user-created contents based on the computed user reputation.