Automated Content Moderation via Machine Learning Filtering
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Solution Overview
Problem
Social networking systems face challenges in effectively moderating online forum content, as manual deletion of inappropriate comments is inefficient and limiting user access can restrict diverse viewpoints, exposing users to inappropriate content before moderation can occur.
Innovation Solution
Implementing a social networking system that analyzes comment text and sentiment to block profane, negative, or racist content, using a machine learning classifier trained on moderator actions to automatically filter out prohibited comments, while allowing them to be visible only to the commenting user and their friends, and restricting repeat offenders from posting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual deletion of inappropriate comments is used, then inappropriate content can be removed, but users are exposed to banned content before deletion and the process is inefficient
Solution Approach 1:
The system performs preliminary filtering of comments before they are displayed to users. The filtering engine analyzes comments in real-time and blocks inappropriate content from appearing in the forum, preventing user exposure to banned content before moderators need to intervene.
Solution Approach 2:
The patent replaces manual mechanical moderation with an automated electronic filtering system. The filtering engine uses computer algorithms to automatically detect and block inappropriate comments, substituting human moderators' manual review process with automated text analysis and pattern recognition.
2Reliability
If users are limited to certain social networks for commenting, then content requirements can be enforced, but diverse viewpoints are restricted
Solution Approach 1:
The filtering engine acts as an intermediary between users and the forum content. Instead of restricting which users can comment, the system allows all users to comment but filters the content through an automated intermediary that blocks only inappropriate remarks while permitting diverse viewpoints to pass through.
Solution Approach 2:
The system changes the parameter being controlled from user identity (which users can comment) to content characteristics (which comments are appropriate). By filtering based on content parameters such as profanity, hate speech, and relevance rather than user source, the system maintains diverse viewpoints while enforcing content requirements.
3Object-affected harmful factors
If blocking certain comments is implemented, then inappropriate content is prevented from display, but the system complexity increases
Solution Approach 1:
The moderation system is segmented into distinct functional modules: a filtering engine for real-time comment analysis, a machine learning classifier for pattern recognition, and a content database for reference material. This segmentation allows the complex moderation task to be divided into manageable components that can be developed and maintained independently.
Solution Approach 2:
The filtering engine performs self-service by automatically analyzing and blocking inappropriate comments without requiring constant human intervention. The system uses automated algorithms to identify and filter prohibited content, reducing the operational complexity of manual moderation while maintaining effective content control.
Data Source
AI summary
Users of social networking system are provided with user interface elements permitting the user to post comments on pages within the social networking system. Pages may be provided for any non-user entity, including for example, pages for businesses, products, concepts, etc. Embodiments provided herein permit page moderators to ban certain content from being displayed on a page. For example, the social networking system may receive a list of proscribed content and block comments containing the proscribed content by reducing the distribution of those comments to other viewing users. However, the social networking system may display the blocked content to the commenting user such that the commenting user is not made aware that his or her comment was blocked, thereby providing fewer incentives to the commenting user to spam the page or attempt to circumvent the social networking system filters.