Display System for Real-Time Derivative Issue Detection
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Solution Overview
Problem
Existing network public opinion analysis systems rely on keyword-based searches, which are time-consuming and inefficient for real-time analysis, often missing derivative issues and requiring human intervention, leading to non-real-time and incomplete coverage of evolving online discussions.
Innovation Solution
A display system and method that automatically identifies and aggregates related topics by analyzing co-occurrence correlations and social voice metrics, determining derivative issues through overlap rates and social voice evaluations, and displaying them based on time-based characteristics without human labor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If keyword-based search is used for public opinion analysis, then the system can identify original issues, but it cannot automatically detect derivative issues and requires manual intervention
Solution Approach 1:
The patent replaces manual keyword-based analysis with an automated computational system that uses co-occurrence correlation algorithms and social voice metrics to automatically detect and classify derivative issues, eliminating the need for human intervention in issue identification
Solution Approach 2:
The patent introduces intermediate indicators including co-occurrence correlation coefficients, social voice metrics, and overlap rates as mediators between raw web page data and derivative issue identification, enabling automatic detection through quantitative analysis
2Reliability
If manual identification and aggregation of related topics is performed, then coverage of derivative issues can be improved, but it is time-consuming and non-real-time
Solution Approach 1:
The patent implements continuous automated monitoring and analysis of web pages, maintaining real-time tracking of issue evolution through ongoing calculation of co-occurrence correlations and social voice metrics, eliminating gaps caused by manual analysis intervals
Solution Approach 2:
The system performs self-service by automatically collecting, analyzing, and interpreting web page data without human intervention, using algorithms to autonomously identify derivative issues and generate analysis results
3Loss of information
If keyword-based searching is used, then original issues can be found, but derivative issues are missed due to keyword changes
Solution Approach 1:
The patent changes the analysis parameters from fixed keywords to dynamic indicators including co-occurrence correlation coefficients, social voice metrics, and overlap rates, allowing the system to detect derivative issues even when specific keywords change by analyzing quantitative relationships
Data Source
AI summary
A display system for an issue comprises an input unit, a display unit and an processing unit. The input unit receives an initial keyword corresponding to an issue. The display unit displays at least a derivative issue generated from the issue during a time period according to time-based characteristics. The processing unit coupled to the input unit and the display unit obtains tags of subject contents of web pages, and obtains a present keywords group according to co-occurrence correlation of the tags. The processing unit analyzes the correlation between the present keywords calculated based on social voice, analyzing overlap rate for the present keywords compared with the initial keywords, and compares correlation between the present keywords with correlation between the initial keywords calculated based on social voice, in order to determine whether at least one of the derivative issue is generated.