Social Opinion Categorization and Ranking System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods do not effectively categorize, rank, and present social media opinions as answers to questions in a drill-down or filterable manner, leading to users having to manually review and interpret numerous opinions, which can result in missed valuable information or incorrect weighting due to lack of evidence awareness.
Innovation Solution
A method that analyzes questions to determine possible answer categories, extracts and categorizes social media opinions, computes opinion strength using responder-specific language, cultural, experience, and evidentiary support models, and ranks opinions for filterable presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If social media opinions are presented without categorization and ranking, then all opinions are available to users, but users must manually review and interpret numerous opinions, leading to loss of time and potential missed valuable information
Solution Approach 1:
The patent segments opinions into distinct categories based on the type of information they contain (e.g., factual, opinion-based, experiential). This segmentation allows users to quickly locate relevant information without reviewing all opinions, thereby reducing time loss while preventing valuable information from being missed.
Solution Approach 2:
The system performs preliminary categorization and ranking of opinions before presentation to users. By pre-organizing opinions according to their informational value and relevance, the system eliminates the need for manual review of all opinions, thus reducing time loss while ensuring valuable information is not overlooked.
2Measurement precision
If opinions are presented without strength computation and ranking, then all opinions are shown equally, but users cannot identify strong, evidence-supported opinions, leading to incorrect weighting
Solution Approach 1:
The patent replaces manual human judgment with an automated computational system that calculates opinion strength based on multiple parameters including evidence quality, responder credibility, and consensus metrics. This substitution provides precise measurement of opinion strength while maintaining ease of operation, as users can readily identify strong opinions through the computed rankings without manual evaluation.
3Extent of automation
If a comprehensive analysis system is implemented to categorize and rank opinions, then opinion evaluation becomes automated and precise, but system complexity increases
Solution Approach 1:
The complex opinion analysis system is segmented into distinct functional modules: categorization module, strength computation module, ranking module, and presentation module. Each module handles a specific aspect of the analysis, making the overall complex system manageable and maintainable while achieving high automation in opinion evaluation.
Solution Approach 2:
The patent implements a universal framework that handles multiple types of opinions across different categories using the same core analysis mechanisms. This multi-functionality allows the system to achieve comprehensive automation without proportionally increasing complexity, as the same modular components serve multiple purposes across different opinion types.
Data Source
AI summary
A question is analyzed to determine a set of categories, a category corresponding to a type of possible answers responsive to the question. A set of opinions is extracted from social media data. Each opinion is from a corresponding responder on a social media platform to which the question is sent. An opinion from the set of opinions is categorized into a category from the set of categories. A strength of the opinion is computed using a subset of a set of strength parameters. The opinion is ranked according to the strength of the opinion. The opinion, the strength, and the category are presented in a filterable presentation.