Social Media Content Filtering Engine for Impact Assessment
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Solution Overview
Problem
Existing systems fail to accurately assess the impact of social media content on organizations due to their reliance on simplistic positivity/negativity evaluations, neglecting context, demographic characteristics, and cultural differences, leading to inaccurate interpretation and potential misinterpretation of customer engagement.
Innovation Solution
A computer-implemented system that filters and scores social media content based on multiple criteria, including demographic and locality factors, using a filtering engine and scoring engine to determine a total score that indicates positive or negative impact, considering metadata and context to provide a nuanced assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a filtering system evaluates content based on a list of positive or negative words, then the evaluation process is simple and fast, but the accuracy of interpreting the true sentiment and impact of the content deteriorates
Solution Approach 1:
The patent segments the evaluation process into multiple independent filtering stages (demographic filter, cultural filter, context filter, locality filter) that each analyze specific aspects of the content separately, then combine their results. This allows comprehensive analysis without sacrificing speed, as each segment can be processed independently and in parallel.
Solution Approach 2:
The patent adds multiple new dimensions to the evaluation process beyond simple positive/negative word detection. These include demographic dimensions (age, gender, ethnicity), cultural dimensions (cultural background, language), contextual dimensions (conversational context, sarcasm detection), and locality dimensions (geographic location). This multi-dimensional approach dramatically improves accuracy while maintaining efficiency through structured processing.
2Measurement precision
If a filtering system considers multiple factors including demographic and cultural context, then the accuracy of content interpretation improves, but the complexity of the system increases
Solution Approach 1:
The patent divides the complex filtering system into separate, modular filter components (demographic filter 410, cultural filter 420, context filter 430, locality filter 440). Each filter handles a specific aspect of analysis independently, making the overall complex system manageable through modular design. This segmentation allows each component to be optimized separately while maintaining overall system efficiency.
Solution Approach 2:
The patent creates a universal filtering framework that can handle multiple types of analysis (demographic, cultural, contextual, locality) through a single multi-functional system architecture. The scoring engine 600 universally processes outputs from all filter types using the same algorithmic approach, providing consistency across diverse analysis dimensions while managing complexity through standardized processing.
3Productivity
If a filtering system filters out negative words, then the processing is efficient, but the actual meaning and nuance of the content is lost
Solution Approach 1:
Instead of filtering out negative words as the patent describes conventional systems do, this patent inverts the approach by actively analyzing and preserving negative content through dedicated filters. The cultural filter 420 and context filter 430 specifically examine negative expressions to understand their true meaning in context, preventing loss of important information while maintaining processing efficiency through targeted analysis rather than blanket filtering.
Solution Approach 2:
The patent introduces intermediary filtering layers (demographic filter 410, cultural filter 420, context filter 430, locality filter 440) that stand between the raw content and final evaluation. These intermediaries preserve and analyze negative words by translating them into contextualized meaning scores, preventing information loss while maintaining processing efficiency through structured intermediate analysis rather than direct filtering.
Data Source
AI summary
A computing system and method are provided for impact assessment and treatment of social media content, the system operating on social media content received at a social media conveyance computing system. The system includes at least one computer memory storing filtering rules and scoring rules, the score indicating a degree of negative impact of the social media content. The system additionally includes an information capture system for receiving a social media stream, the social media stream including multiple messages and a pre-processing computing system for processing the messages in the social media stream and extracting metadata related to each message. The system further includes a filtering and scoring computing system for receiving each message and associated metadata from each. The filtering and scoring computing system filters and scores the content and determines a degree of negative impact.