Content Moderation System Using Multi-Dimensional Reliability Scoring
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Solution Overview
Problem
Fake news dissemination undermines serious media coverage and makes it difficult for journalists to cover significant news stories due to the spread of deliberate misinformation.
Innovation Solution
A content moderation system that analyzes electronic documents to determine reliability scores, including content, author, and domain reliability, to identify and flag unreliable content, thereby reducing the propagation of fake news.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple reliability measures (content, author, domain scores) are combined to accurately identify fake news, then the reliability of content moderation improves, but the system complexity increases
Solution Approach 1:
The system segments the reliability assessment into three independent components: content reliability score (analyzing document features like sentiment, summary, multimedia), author reliability score (evaluating author credentials and publication history), and domain reliability score (assessing the hosting website's credibility). Each component is calculated separately using dedicated algorithms, then combined to form an overall reliability assessment. This segmentation allows complex moderation to be broken into manageable, specialized sub-tasks.
Solution Approach 2:
The content moderation system serves multiple functions through a single integrated platform: it evaluates content quality, verifies author credentials, assesses domain credibility, detects fake news, and provides reliability scoring. By consolidating these diverse functions into one system that processes electronic documents comprehensively, the patent achieves high reliability content moderation without requiring separate specialized systems for each function.
2Measurement precision
If comprehensive analysis of electronic document features is performed to determine reliability scores, then the accuracy of fake news detection improves, but the processing time increases
Solution Approach 1:
The system performs preliminary analysis by first evaluating the domain reliability score and author reliability score before conducting the full content analysis. If the domain or author is already identified as unreliable through preliminary checks, the system can flag the document as potentially fake news without completing the entire comprehensive analysis pipeline. This preliminary action reduces processing time for obvious cases while maintaining detection accuracy.
Solution Approach 2:
The system implements tiered analysis where not all documents receive the full extent of analysis. For documents from highly reliable domains and authors, the system may perform lighter content analysis. Conversely, for documents from questionable sources, the system applies more rigorous analysis. This partial action approach optimizes processing time by adapting the analysis depth to the specific document's risk profile while maintaining overall detection accuracy.
Data Source
AI summary
This document describes systems, methods, devices, and other techniques for performing content moderation. In some implementations, a computing device receives input data in relation to an electronic document. The computing device generates, based on the received input data, data representing one or more features of the electronic document and analyzes the generated data representing one or more features of the electronic document to determine one or more reliability scores indicating respective measures of reliability of the electronic document. The reliability scores include one or more of (i) a content reliability score, (ii), an author reliability score, and (iii) a domain reliability score. The computing device indicates, based on one or more of the reliability scores, whether the electronic document is reliable or not.