Social Graph Comment Ordering System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing user comment systems on social networking platforms fail to effectively order and present comments based on social graph information and user attributes, leading to irrelevant comments being prioritized over relevant ones, which can diminish user engagement and interaction.
Innovation Solution
A user comment system that retrieves comments associated with content objects, orders them by time value, adjusts the order based on social graph information of the user, and presents the adjusted list to the user, incorporating weighting scores for comments from friends and trusted users to prioritize relevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comments are ordered by time value only, then the system is simple and fast, but relevant comments from trusted users are not prioritized
Solution Approach 1:
The patent changes the ordering parameter from simple time value to a composite relevance score that incorporates multiple factors including social graph distance, user trustworthiness, and comment recency. This transforms the sorting criterion from a single parameter to a multi-parameter weighted system, improving comment relevance while accepting increased computational complexity.
Solution Approach 2:
The patent introduces an intermediary relevance scoring mechanism that mediates between the simple time-based ordering and the complex social graph analysis. The relevance score acts as an intermediary metric that combines multiple factors (social distance, trustworthiness, recency) into a single ordering value, simplifying the final sorting operation while capturing complex relationships.
2Productivity
If comments from all users are treated equally, then the system is fair and simple, but user engagement decreases due to irrelevant comments
Solution Approach 1:
The patent applies local quality by assigning different weights to different users based on their individual characteristics (trustworthiness scores, social relationship distance). Instead of uniform treatment, each user's comments are evaluated with localized weighting factors that reflect their specific relationship to the viewing user, thereby improving engagement through personalized relevance.
3Reliability
If social graph information is used to order comments, then relevant comments are prioritized, but user privacy settings may be compromised
Solution Approach 1:
The patent performs preliminary action by checking privacy settings and computing social graph distances only for users whose privacy permissions allow such analysis. The system pre-evaluates which users can be safely included in the social graph analysis based on their privacy configurations, thereby protecting user privacy while still enabling relevant comment ordering for permitted users.
Data Source
AI summary
In one embodiment, a social networking system receives a request by a first user for user comments associated with a content object, accesses a data store of user comments to retrieve a set of user comments associated with the content object, orders the set of user comments based on a time value associated with each comment of the set of user comment, adjusts the order of user comments based on social graph information of the first user, and presents the adjusted list of user comments to the first user.