Social Data Filtering System Using Metadata and Text Filters
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Solution Overview
Problem
Current approaches for monitoring social media content are inefficient and time-consuming, requiring businesses to sift through vast amounts of data to identify relevant information, often resulting in inaccurate and unfiltered data that does not meet specific organizational needs.
Innovation Solution
A system and method that integrate enterprise applications with social networking platforms, utilizing metadata and text-based filters to analyze social media data, annotate messages with topic identifiers, and categorize content based on filter criteria, enabling more precise and efficient identification of topics of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sifting through social media content is used to identify relevant information, then businesses can identify topics of interest, but the process becomes extremely time-consuming and inefficient
Solution Approach 1:
The patent replaces the manual mechanical process of sifting through social media content with an automated computer-based system that uses metadata filters and text-based filters to efficiently identify and categorize relevant information, thereby resolving the contradiction between accuracy and time consumption
Solution Approach 2:
The system enables automated self-service filtering and categorization of social media content through predefined metadata filters and text-based filters, eliminating the need for manual intervention while maintaining high accuracy in identifying relevant topics
2Measurement precision
If comprehensive filtering of social media data is implemented to improve accuracy, then data relevance improves, but the system complexity increases
Solution Approach 1:
The patent segments the filtering system into two distinct components: metadata filters that operate on structured data fields, and text-based filters that operate on content fields. This segmentation allows each filter type to specialize in specific filtering tasks, improving overall accuracy while keeping individual filter components relatively simple and manageable
Solution Approach 2:
The system introduces an intermediary layer that separates filter definition from filter execution. Metadata filters and text-based filters act as intermediaries between the raw social media data and the final categorized output, enabling complex filtering logic to be implemented through simple, configurable filter rules without increasing system complexity
3Productivity
If automated filter-based topic creation is implemented, then productivity increases, but the ease of operation decreases due to complex filter configuration
Solution Approach 1:
The patent implements dynamic filter configuration where metadata filters and text-based filters can be easily added, removed, or modified based on changing business needs. The system adapts to different filtering requirements without requiring complex reconfiguration, maintaining ease of operation while improving productivity through automated processing
Solution Approach 2:
The filtering system is designed with universal metadata filters and text-based filters that can be applied across different social media platforms and content types. This multi-functionality allows the same filter framework to handle diverse filtering scenarios, improving productivity without requiring platform-specific complex configurations
Data Source
AI summary
Disclosed is a system, method, and computer program product for performing semantic analysis and creating topics with regards to social data. A user interface is provided that allows the user to view and interact with to view and control the process/mechanism or creating topics. The user interface allows the user to create one or more text-based filters and metadata filters based on which social data for each topic is filtered.