Dynamic Theme Analysis for Social Data
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Solution Overview
Problem
Conventional technologies face difficulties in automating the process of identifying the subject matter in social media messages due to the wide range of terms and terminology used by users, making it challenging to understand the significance of social media data effectively.
Innovation Solution
A system and method for performing dynamic theme analysis on social media data across multiple internet-based sources, utilizing semantic analysis and user interaction to identify and filter themes, allowing users to create and refine topic definitions through a user interface with features like 'More Like This' and 'Less Like This' buttons, and employing a volatility index to determine the scope of the topic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional technologies are used to identify subject matter in social media messages, then the process can be automated, but the accuracy of identifying the correct subject matter deteriorates due to the wide range of terms and terminology used by users
Solution Approach 1:
The patent introduces an intermediary theme identification process between raw social media data and final subject matter classification. Themes serve as intermediate concepts that bridge the gap between diverse user terminology and standardized subject matter categories, enabling automated processing while maintaining accuracy through multiple layers of semantic interpretation
Solution Approach 2:
The patent adds a thematic dimension to the subject matter identification process. Instead of directly mapping user terms to subject matter categories, the system first identifies themes as an intermediate dimension, then maps themes to subject matter. This dimensional transformation allows the system to handle terminology diversity by operating in the theme space where semantic relationships are more structured
2Measurement precision
If dynamic theme analysis is performed on social media data, then the understanding of social media data becomes more accurate and comprehensive, but the complexity of the system increases due to semantic analysis and user interaction requirements
Solution Approach 1:
The patent segments the complex theme analysis system into distinct functional modules: data collection module, theme identification module, volatility calculation module, and user interaction module. Each module handles a specific aspect of the analysis, making the overall complex system manageable through modular design where each segment can be developed, tested, and maintained independently
Solution Approach 2:
The system incorporates self-service mechanisms where the volatility index automatically adjusts theme scope based on data characteristics without requiring manual system reconfiguration. The semantic analysis engine autonomously identifies themes and their relationships, reducing the operational complexity burden on users while maintaining high analysis accuracy
3Measurement precision
If users are allowed to interact with the system to refine topic definitions, then the relevance of captured subject matter improves, but the time required to achieve accurate results increases
Solution Approach 1:
The system performs preliminary theme identification and volatility calculation before user interaction begins. By pre-processing the data to establish initial themes and their volatility metrics, the system provides users with a head start, reducing the number of interaction iterations needed to achieve accurate subject matter capture while maintaining high relevance
Solution Approach 2:
The volatility index serves as a feedback mechanism that automatically adjusts theme scope based on the diversity and distribution of social media data. This continuous feedback loop allows the system to self-optimize during user interaction, providing real-time guidance that reduces the time users need to spend refining topic definitions while maintaining high subject matter relevance
Data Source
AI summary
Disclosed is a system, method, and computer program product for performing dynamic theme analysis 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 for performing theme analysis.