Real-Time Profanity Detection via Weighted Word Scoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing social media platforms face challenges in identifying profanity in real-time within textual content to determine its appropriateness for publication, as they lack effective methods to assess and alert users during content creation.
Innovation Solution
A computer-implemented method and system that detects profanity levels in 140-character textual posts by identifying words, assigning weights based on database presence, calculating a net profanity factor, and deciding on publication, with options for routing to moderators or quarantining content, utilizing proprietary databases and AI-driven algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional social media platforms allow users to freely express and publish content in various formats, then user expression freedom is improved, but the ability to identify and control profanity in real-time deteriorates
Solution Approach 1:
The system performs preliminary profanity detection and analysis before content is published. By calculating profanity scores and identifying inappropriate content in advance of publication, the system maintains user expression freedom while ensuring profanity is detected and controlled beforehand, resolving the contradiction between free expression and reliable profanity identification.
Solution Approach 2:
The patent introduces an intermediary profanity detection system that acts as a mediator between user content creation and publication. This intermediary layer analyzes content for profanity without restricting user expression, providing a bridge that maintains both user freedom and content appropriateness through automated scoring and moderation mechanisms.
2Ease of operation
If profanity detection is performed after content creation, then user expression freedom is maintained, but real-time profanity identification and control deteriorates
Solution Approach 1:
The system performs profanity detection as a preliminary action during the content creation process itself, rather than after publication. By calculating profanity scores in real-time as users type or before they submit content, the system eliminates time loss while maintaining ease of operation, allowing users to receive immediate feedback without post-publication delays.
Solution Approach 2:
The patent implements a feedback mechanism that provides real-time profanity score information to users during content creation. This immediate feedback allows users to adjust their content before publication, achieving both ease of operation and real-time detection by informing users of profanity levels as they compose their messages.
3Productivity
If automated profanity detection systems are implemented, then real-time detection capability is improved, but the need for manual moderator review increases system complexity
Solution Approach 1:
The patent segments the moderation process into distinct stages: automated profanity detection, scoring, threshold evaluation, and conditional routing to human moderators. By dividing the system into modular components with clear decision points, it maintains high real-time detection efficiency while managing complexity through structured, rule-based automation that only escalates to human review when necessary.
Solution Approach 2:
The system implements self-service automation where the profanity detection algorithm independently evaluates content, calculates scores, and makes publication decisions based on predefined thresholds. This self-service capability handles the majority of cases without human intervention, improving productivity while reducing the burden on moderators to review every piece of content, thus managing system complexity effectively.
Data Source
AI summary
A computer implemented method and system for detecting a profanity level of a 140-character textual post generated by a user within one or more communities includes: identifying all words present in the 140-character textual post; assigning a weight to each identified word based on whether or not each identified word occurs in one or more databases; calculating a net profanity factor for each identified word based on the assigned weight; calculating a sum of net profanity factors of all the identified words; and publishing or not publishing the 140-character textual post based on the sum of net profanity factors.