Topic Extraction and Sentiment Analysis for Feedback Mining
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Solution Overview
Problem
Users face difficulties in identifying relevant information about products and services from a large volume of comments and feedback across multiple community forums, requiring manual scanning which is time-consuming and inefficient.
Innovation Solution
A system employing topic extraction and sentiment analysis methods, using techniques like Latent Dirichlet Allocation (LDA) and natural language processing, automatically identifies key phrases and classifies sentiments to extract and rank topics, facilitating automatic evaluation and presentation of feedback trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual scanning of comments and feedback is used, then users can read and understand individual comments, but the process becomes time-consuming and inefficient when dealing with large volumes of data
Solution Approach 1:
The patent replaces manual mechanical scanning of feedback with automated computer-based topic extraction and sentiment analysis systems. The system uses natural language processing algorithms to automatically identify topics, extract key phrases, and analyze sentiments from large volumes of feedback data, eliminating the need for manual reading while maintaining analysis accuracy.
Solution Approach 2:
The system enables self-service feedback analysis where the automated system processes and analyzes feedback data independently without human intervention. The topic extraction and sentiment analysis algorithms automatically operate on incoming feedback, generating insights and reports without requiring users to manually scan through individual comments.
2Productivity
If automated topic extraction and sentiment analysis are implemented, then processing efficiency improves and manual effort is reduced, but the system complexity increases
Solution Approach 1:
The patent segments the feedback analysis system into distinct functional modules: topic extraction module, sentiment analysis module, and feedback processing module. Each module performs a specific function independently, making the overall complex system more manageable and easier to implement. The topic extraction identifies key phrases while the sentiment analysis module separately evaluates emotional tone.
Solution Approach 2:
The system introduces an intermediary processing layer that bridges raw feedback data and actionable insights. The topic extraction and sentiment analysis algorithms act as intermediaries that automatically transform unstructured feedback into structured analysis results, simplifying the interface between data input and business decision-making.
3Quantity of substance
If feedback data from multiple community forums is collected, then the quantity and diversity of information increases, but the difficulty of identifying relevant information increases
Solution Approach 1:
The patent extracts and isolates relevant information from the vast amount of feedback data through automated topic extraction algorithms. The system identifies and extracts key phrases, topics, and sentiment patterns from multiple community forums, separating meaningful insights from irrelevant noise. This extraction process enables users to focus only on processed and relevant information.
Solution Approach 2:
The system changes the parameters of feedback data organization by transforming raw text data into structured categories based on extracted topics and sentiments. The feedback is reorganized according to identified topics (e.g., product quality, delivery, customer service) and sentiment polarity, making relevant information easily detectable and measurable across multiple forums.
Data Source
AI summary
Methods, apparatus, and systems to determine a niche market of items or services, the first phase of which identifies a gap between demand and supply for a set of items. Session logs may be evaluated to compare transactions involving a specific item to those of a larger group of items. The resultant information identifies areas of high demand, but with low availability. The niche market information may be provided as direct merchandising items for sellers. In one example, the method generates niche market item web pages in specific categories. Additional methods, apparatus, and systems are disclosed.