Sentiment-Based Web Content Filtering for Parental Control
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Solution Overview
Problem
Conventional web content filtering methods are error-prone and ineffective in categorizing web pages based solely on predefined words or phrases, particularly for dynamic user-generated content and nuanced parental control policies that require distinctions beyond simple categorization.
Innovation Solution
A sentiment-based filtering system that combines fact-based categorization with sentiment analysis to determine the emotional tone, extremity, and subjectivity of web content, allowing parents to define policies that filter access based on these criteria, enabling more granular control over children's online content exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fact-based categorization is used to filter web content, then the filtering process is simple and fast, but misclassifications occur and nuanced parental control policies cannot be enforced
Solution Approach 1:
The patent combines fact-based categorization with sentiment-based analysis into a unified filtering system. The fact-based engine identifies predefined categories while the sentiment-based engine analyzes emotional tone, extremity, and subjectivity. These two engines work together to provide both simplicity and accuracy, resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The filtering system is divided into separate modules: a fact-based categorization engine and a sentiment-based analysis engine. Each engine handles specific aspects of content analysis independently, then their results are integrated. This segmentation allows the system to maintain simplicity in individual components while achieving high accuracy through their combination.
2Measurement precision
If manual review of web pages is performed to improve categorization accuracy, then misclassifications are reduced, but the process becomes time consuming and expensive
Solution Approach 1:
The sentiment-based analysis engine automatically analyzes web content for emotional tone, extremity, and subjectivity without requiring human intervention. The system serves itself by using algorithmic sentiment analysis to achieve accurate categorization, eliminating the need for time-consuming manual reviews while maintaining high precision.
3Ease of operation
If simple yes-or-no category blocking is used, then the filtering policy is easy to enforce, but nuanced parental control policies cannot be implemented
Solution Approach 1:
The patent adds new dimensions to content filtering by analyzing emotional tone, extremity, and subjectivity alongside traditional category classification. This multi-dimensional approach allows parents to create nuanced policies (e.g., blocking only extremely negative content in the news category) while maintaining ease of operation through a unified policy enforcement mechanism that evaluates all dimensions simultaneously.
4Productivity
If conventional categorization is used for dynamic user-generated content, then the filtering process is fast, but it fails to capture changing focus and tone of blogs and social media
Solution Approach 1:
The sentiment-based analysis engine continuously monitors and re-evaluates dynamic user-generated content as it changes. Unlike conventional categorization that works on static snapshots, the sentiment engine can detect changing focus and tone in real-time, maintaining both filtering speed and accuracy for evolving content like blogs and social media posts.
Data Source
AI summary
A filtering policy is defined responsive to parental directives. The filtering policy specifies to filter a child's access to content based on fact-based categorization and subjective factors, such as the emotional tone, expressed sentiment, extremity and/or expressed subjectivity. Content is categorized based on the occurrence of predefined words. A sentiment-based analysis of content is also performed. The categorization and/or analysis can occur prior to a child's attempt to download the content, or in real-time in conjunction with a download attempt. Attempts by the child to access content are detected. It is determined whether the filtering policy permits the child to access the content in question, responsive to results of the categorization and sentiment-based analysis of that content. If so, the attempted access is allowed to proceed. If not, the access attempt is blocked.