Sentiment Score Unification via Normalization and Weighting
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Solution Overview
Problem
Current customer relationship management (CRM) systems fail to effectively leverage unstructured sentiment data from various sources like social media and message boards due to the lack of a unified approach to integrate and score sentiment expressions, resulting in inconsistent and less accurate sentiment analysis.
Innovation Solution
A sentiment score unification system that includes a processor and storage device to execute multiple sentiment scoring applications, generating respective scores and a unified score through a normalization and weighting process, allowing for a comprehensive and accurate sentiment analysis across different platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sentiment scoring applications with different algorithms are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the sentiment analysis task into multiple independent scoring applications, each handling specific aspects of sentiment evaluation. Multiple sentiment scoring applications execute independently on the same sentiment expressions, with each application contributing a specialized score based on its unique algorithmic approach.
Solution Approach 2:
The system combines multiple independent sentiment scores from different applications into a single unified sentiment score through a normalization and weighting process. The sentiment unification module aggregates the diverse scores by normalizing them to a common scale and applying weighted combinations to produce the final unified sentiment score.
2Measurement precision
If multiple sentiment scores are integrated through normalization and weighting, then measurement precision is improved, but loss of information increases
Solution Approach 1:
The system transforms multiple sentiment scores with different scales and distributions into a unified parameter space through normalization. Each sentiment score is converted to a standardized range, and weighting factors are applied to adjust the influence of different scoring applications, preserving the essential information while enabling meaningful aggregation.
Data Source
AI summary
A sentiment score unification system includes a storage device configured to store a plurality of sentiment scoring applications and a sentiment unification module. The sentiment score unification system further includes a processor in communication with the memory device. The processor may be configured to receive a plurality of sentiment expressions and execute each of the plurality of sentiment scoring applications. Each of the plurality of sentiment scoring applications is executable to generate a respective sentiment score based on the plurality of sentiment expressions. Each respective sentiment score is indicative of a level of sentiment. The processor is further configured to execute the sentiment unification module. The sentiment unification module is executable to generate a single unified sentiment score based on the respective sentiment scores. A method and computer-readable medium are also disclosed.