Sentiment Analysis System Using Term Segmentation
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Solution Overview
Problem
Existing online platforms lack an effective method to analyze and quantify user sentiment from user-generated text content, relying on simplistic like/dislike ratings rather than nuanced sentiment analysis from words, phrases, and sentences.
Innovation Solution
A system and method for determining sentiment by analyzing user-generated text content, identifying relevant terms, and assigning sentiment scores based on their context, which can be multi-dimensional and reflect intensity, using a combination of term extraction, grammatical analysis, and relevance determination to provide a comprehensive sentiment value for subjects and categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simplistic like/dislike ratings are used, then the system is easy to operate, but the measurement precision of user sentiment is insufficient
Solution Approach 1:
The patent segments the text content into individual terms and assigns sentiment scores to each term separately. This segmentation allows for precise measurement of user sentiment by analyzing specific words rather than treating the entire text as a single unit, thereby improving measurement precision while maintaining manageable system complexity through modular processing.
Solution Approach 2:
The patent introduces an intermediary sentiment scoring system that bridges the gap between simple like/dislike ratings and complex natural language understanding. By using predefined sentiment scores for different terms and combining them mathematically, the system achieves high measurement precision without requiring full artificial intelligence complexity.
2Measurement precision
If term extraction and grammatical analysis are performed, then the sentiment analysis accuracy is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-defining sentiment scores for various terms before actual sentiment analysis is needed. This allows the system to quickly retrieve and combine predefined scores during processing rather than performing complex grammatical analysis in real-time, thereby improving accuracy while reducing processing time through advance preparation.
Solution Approach 2:
The patent applies partial action by focusing grammatical analysis only on relevant portions of text that contain sentiment-bearing terms, rather than analyzing the entire text structure. This selective approach maintains high sentiment analysis accuracy while minimizing the time consumed by grammatical processing.
3Loss of information
If multi-dimensional sentiment scores are calculated, then the information completeness is improved, but the device complexity increases
Solution Approach 1:
The patent applies dimensionality change by introducing multiple sentiment dimensions (positive, negative, neutral scores) rather than using a single sentiment value. This allows comprehensive capture of user sentiment information while maintaining relatively simple calculation structures based on predefined term scores, thereby improving information completeness without excessive complexity increase.
Data Source
AI summary
A system and method for determining sentiment from user-generated text content is provided. A sentiment score is determined for one or more terms in a user-generated text content. A sentiment value is determined for the text content that is based at least in part on the sentiment score for the one or more terms.