Social Risk Identification System Using Pre-Trained Classifier
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Solution Overview
Problem
Current technologies fail to accurately identify negative information on social networks, leading to financial risk events for companies due to the rapid spread of misinformation.
Innovation Solution
A system and method that obtain social information from various accounts, analyze it to extract company and product names, resolve the information to extract key points, and use a pre-trained classifier to identify negative content, sending relevant information to a terminal for review.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing technical solutions are used for identifying network information, then the identification process is simple, but the accuracy of identifying negative information is insufficient
Solution Approach 1:
The patent segments the identification process into multiple modules: obtaining social information from networks, analyzing information to extract company/product names, resolving information to obtain key points, and classifying information using a pre-trained classifier. This segmentation allows each module to specialize in specific tasks, improving overall identification accuracy while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent introduces a pre-trained classifier as an intermediary component that bridges the gap between raw social information and risk identification. The classifier is trained on historical data and serves as a specialized mediator to accurately identify negative information, thereby improving measurement precision without requiring the entire system to become overly complex.
2Reliability
If social information is monitored in real-time from multiple accounts, then the coverage of risk detection is improved, but the amount of information to be processed increases
Solution Approach 1:
The patent extracts only the essential elements from social information - specifically company names and product names - using analysis and resolution modules. This extraction process filters out irrelevant content and focuses processing resources on key information, thereby maintaining comprehensive risk detection coverage while reducing the volume of information that requires detailed processing.
Solution Approach 2:
The patent applies partial action by not processing all social information in equal detail. Instead, it focuses processing efforts on information containing company and product names that are relevant to financial risk, using the pre-trained classifier to identify only the most critical negative information. This selective approach maintains high reliability for risk detection while managing information volume efficiently.
Data Source
AI summary
The present disclosure provides a system, a method, an electronic device, and a storage medium for identifying risk event based on social information. The system includes an obtaining module configured for obtaining social information released by various predetermined social accounts from a predetermined social server; an analysis module, configured for analyzing the social information to obtain a company name and/or a product name contained in the social information; a resolution module configured for, after the company name and/or product name contained in the social information are obtained, resolving the social information to obtain key point information corresponding to the social information; and an identifying module configured for identifying an information directing classification corresponding to the key point information using a pre-trained classifier such that the social information corresponding to the predetermined information directing classification and the social account releasing the social information are sent to a predetermined terminal.