Social Network Question Targeting via Tag Affinity
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Solution Overview
Problem
Traditional question and answer systems on social networking platforms face challenges in delivering relevant and accurate answers due to the lack of expertise verification among users and inefficient tagging, leading to overwhelming and duplicative content, which discourages user engagement.
Innovation Solution
A system that automatically tags questions based on keywords and user-selected tags, prioritizes answers based on social information and user affinities, and targets questions to users connected through their interests and interactions, enhancing the relevance and accuracy of responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users can answer any question without expertise verification, then user engagement increases, but answer quality and accuracy deteriorate
Solution Approach 1:
The patent introduces an expertise verification system as an intermediary between users and questions. The system automatically verifies user expertise by analyzing user profiles, answer history, and interactions with the question topic, thereby ensuring answer quality while maintaining ease of participation.
Solution Approach 2:
The system performs automatic expertise verification by analyzing user-generated content and profile information without requiring manual review. This self-service approach maintains high user engagement while ensuring answer quality through automated assessment of user credentials and historical performance.
2Measurement precision
If manual tagging by moderators is used, then question classification accuracy improves, but system complexity and operational cost increase
Solution Approach 1:
The system automatically tags questions by extracting keywords and analyzing user-selected tags without requiring manual moderator intervention. The automatic tagging system uses natural language processing to identify relevant topics and classify questions appropriately, maintaining classification accuracy while reducing system complexity.
Solution Approach 2:
The patent replaces the mechanical process of manual tagging with an automated computational system that uses keyword extraction and tag analysis. This substitution eliminates the need for human moderators while maintaining or improving tagging accuracy through consistent algorithmic application.
3Quantity of substance
If all questions are displayed to all users, then information completeness improves, but information relevance and user experience deteriorate
Solution Approach 1:
The system personalizes question distribution by analyzing individual user profiles, interests, and interaction patterns. Each user receives a customized subset of questions that are locally optimized for their specific interests and expertise, rather than receiving all questions uniformly. This ensures information relevance while maintaining access to complete information through the broader system.
Data Source
AI summary
Users of a social networking system post questions for other users to answer. Questions are automatically tagged based on keywords extracted from text within the posted questions as well as user-selected tags. Users also browse questions asked by other users on the social networking system using an interface that displays questions by topics and sub-topics. Answers may be voted on and sorted by social information related to the browsing user. Affinities for tags are recorded based on users' interactions with the question and answer service. Affinities for tags may also be used to target questions to other users and sort answers.