Trend identification systems and methods
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing market research methods struggle to efficiently automate the analysis of social media and news data for meaningful trend identification due to the large volume and variability of user-generated content, limiting the predictive value and efficiency of market insights.
Innovation Solution
A system utilizing transformer-based LLMs and AI/ML models for data preprocessing, hierarchical organization, predictive modeling, and dashboard visualization to automate the categorization and analysis of social media and news data, enabling deeper market insights and predictive market information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated data analysis tools are used to process social media data, then productivity increases, but measurement precision and accuracy of trend identification deteriorate due to the complexity and variability of user-generated content
Solution Approach 1:
The patent segments the data analysis process into multiple hierarchical levels: data collection, data preprocessing, topic modeling, trend identification, and visualization. Each segment handles specific aspects of the complex data, allowing automated processing while maintaining precision through specialized algorithms at each stage.
Solution Approach 2:
The patent introduces intermediary components including NLP processors, topic models, and feature extractors that mediate between raw social media data and final trend insights. These intermediaries simplify the data transformation process while preserving meaningful patterns, enabling both automation and accuracy.
2Quantity of substance
If more data from social networks is collected to improve market insights, then the quantity of information increases, but the difficulty of organizing and categorizing the data increases
Solution Approach 1:
The patent organizes the vast quantity of data into segmented categories through hierarchical topic models and classification systems. Data is divided into topics, sub-topics, and trend categories, making the organization of large datasets manageable and systematic rather than overwhelming.
Solution Approach 2:
The patent employs a universal data processing framework that can handle multiple data types (text, images, videos) and platforms through a single integrated system. The same core algorithms process diverse data formats, reducing the need for separate organization systems for each data type.
3Measurement precision
If manual analysis of social media data is performed to ensure accuracy, then measurement precision improves, but loss of time increases
Solution Approach 1:
The patent implements self-service automated analysis where the system performs data collection, processing, topic modeling, and trend identification without human intervention. The automated algorithms independently analyze data and generate insights, eliminating time-consuming manual analysis while maintaining precision through sophisticated computational methods.
Solution Approach 2:
The patent enables continuous automated data analysis that operates continuously rather than in batches. The system continuously monitors social media data, updates topic models, and identifies emerging trends in real-time, providing ongoing accurate insights without the time interruptions associated with manual analysis cycles.
Data Source
AI summary
Systems and methods are disclosed for market research and social media categorization solutions and methods that are capable of using data from existing social networks, news or reference resources, and other information systems to automate the process of grouping data items into labeled categories by topic. These embodiments can extract greater market insight from available data sources, provide greater predictive value to marketing or sales strategies, and save money by being more efficient or easier to implement into existing systems