Explicit Sentiment Identifier for Online Communication Analysis
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Solution Overview
Problem
Current systems face challenges in accurately identifying and tracking user sentiment in online messages due to complexities in humor, sarcasm, and slang, requiring improved methods for sentiment analysis.
Innovation Solution
A system and method that allow users to input end-user-selected electronic data, specifically Tengrade values, which are correlated to topics, enabling users to easily express and track sentiments through various mechanisms like Twitter, email, and web sites, with data collection and analysis for optimization of systems and processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex algorithms and language processing software are used to deduce user sentiment, then the system can attempt to analyze sentiment, but the accuracy is flawed due to assumptions and complexities of humor, sarcasm, and slang
Solution Approach 1:
The patent introduces an intermediary mechanism where users directly indicate their sentiment through a simplified interface (e.g., selecting from predefined sentiment options or using emoji indicators) rather than relying on complex automated detection. This intermediary layer bridges the gap between raw message input and sentiment data, allowing users to explicitly mark their sentiment state without requiring complex parsing algorithms to interpret nuanced language.
Solution Approach 2:
The system enables users to self-identify and label their own sentiment in messages. Instead of the system attempting to infer sentiment through complex algorithms, users actively participate by marking or tagging their sentiment state. This self-service approach eliminates the inaccuracies of automated detection while keeping the user experience simple and direct.
2Extent of automation
If automated sentiment detection systems are used, then sentiment tracking can be implemented, but the systems are flawed due to assumptions about language and inability to handle humor, sarcasm, and slang
Solution Approach 1:
The patent introduces an intermediary mechanism where users directly indicate their sentiment through a simplified interface (e.g., selecting from predefined sentiment options or using emoji indicators) rather than relying on complex automated detection. This intermediary layer bridges the gap between raw message input and sentiment data, allowing users to explicitly mark their sentiment state without requiring complex parsing algorithms to interpret nuanced language.
Solution Approach 2:
The system incorporates feedback mechanisms where users can correct or refine automated sentiment interpretations by directly indicating their actual sentiment state. This feedback loop allows the system to learn from user corrections and improve its automated detection over time, while also providing immediate accurate sentiment data through direct user input.
3Adaptability or versatility
If complex language processing is used to understand sentiment, then analysis capability is provided, but the process becomes time-consuming and computationally intensive
Solution Approach 1:
The patent extracts the essential sentiment information directly from users through simplified indicators (such as sentiment selectors, emoji tags, or brief sentiment markers) rather than processing the entire message text through complex language models. By taking out only the critical sentiment labeling task from the broader message processing, the system achieves fast and accurate sentiment identification without the time cost of comprehensive linguistic analysis.
Solution Approach 2:
The system segments the message processing task by separating the sentiment identification function from the full text analysis. Users provide sentiment information through discrete, pre-defined categories or indicators, which can be processed independently and rapidly without requiring analysis of the complete message content, thereby reducing processing time while maintaining analytical capability.
Data Source
AI summary
In some embodiments, a user expresses his/her sentiment in a message, blog post, social media post, or other online communication and explicitly identifies that sentiment with a symbol (such as an asterisk). This explicitly identified sentiment is recorded in a database of individual and public opinions.