Public Sentiment Processing System with Sensitivity-Based Access Control
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Solution Overview
Problem
Current public sentiment processing systems have a weak concurrent processing capacity and are unable to exhibit data with different sensitivity levels to users with varying account levels, leading to inefficient data processing and security issues.
Innovation Solution
A system comprising a network data integration platform, a big data cluster, a business data integration platform, and a data exhibition platform that audits and analyzes network public sentiment, filters invalid data, screens enterprise public sentiment, and exhibits it to users based on their account levels, improving data processing efficiency and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If only one distributed relational database is deployed, then the system structure is simple, but the concurrent processing capacity is weak
Solution Approach 1:
The patent divides the database system into multiple distributed relational databases, with each database independently handling a portion of the data and query load. This segmentation enables parallel processing of multiple queries simultaneously, thereby increasing concurrent processing capacity while maintaining manageable system complexity through modular architecture.
2Reliability
If all public sentiment data is displayed to all users, then information completeness is high, but information security and sensitivity control are compromised
Solution Approach 1:
The patent implements differential data display where different user groups receive different subsets of public sentiment data based on their account levels and authorization. Sensitive data is selectively hidden or obscured for lower-level users while being fully visible to higher-level users, thereby maintaining information security without completely blocking data access for any user group.
Solution Approach 2:
The system performs preliminary classification and sensitivity labeling of public sentiment data before storage, categorizing data by sensitivity levels and associated user permissions. This advance preparation enables efficient runtime filtering and selective display based on user credentials, ensuring information security is maintained without requiring complex real-time analysis during data retrieval.
3Productivity
If manual data auditing is performed, then data accuracy is high, but processing efficiency is low
Solution Approach 1:
The patent implements automated auditing mechanisms where the system itself performs data validation, sensitivity classification, and permission verification through pre-configured rules and algorithms. This self-service auditing maintains high data accuracy by consistently applying defined criteria while dramatically improving processing efficiency by eliminating manual review bottlenecks.
Data Source
AI summary
Disclosed are a method and a system for processing public sentiment data, computer storage medium and an electronic device. The system includes: a network data integration platform configured to audit and analyze collected network public sentiment to acquire a sensitivity level of the network public sentiment, and send the network public sentiment and the sensitivity level of the network public sentiment to a big data cluster; the big data cluster configured to send the filtered network public sentiment to a business data integration platform; the business data integration platform configured to screen enterprise public sentiment from the filtered network public sentiment, and store an association relationship among the enterprise public sentiment, an acquired user account level and a sensitivity level of the enterprise public sentiment to a database server; and a data exhibition platform configured to exhibit the enterprise public sentiment with the target sensitivity level to an authenticated user.