Sentiment Analysis Alert for Messaging Systems
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Solution Overview
Problem
Current messaging systems lack the ability to effectively analyze and alert users to sentiment changes in textual messages, leading to potential misinterpretations or missed important emotional cues in communication.
Innovation Solution
A method and system that utilize Natural Language Processing (NLP) to determine sentiment parameters of textual messages, such as anger, disgust, fear, joy, and sadness, and output alerts based on these analyses, allowing users to configure alert thresholds and notification preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sentiment analysis processing is added to messaging system, then communication awareness is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary sentiment analysis component that processes messages between transmission and receipt. This mediator analyzes sentiment parameters (anger, disgust, fear, joy, sadness) and generates alerts without requiring complete system redesign, thus adding emotional cue detection while managing complexity through modular integration.
2Loss of information
If real-time sentiment analysis is performed on all messages, then communication awareness is improved, but processing time increases
Solution Approach 1:
The system performs sentiment analysis selectively rather than on all messages. It applies analysis based on configured thresholds and user preferences, processing only those messages that meet specific sentiment criteria. This partial action approach ensures timely detection of important emotional cues while avoiding unnecessary processing of routine communications.
3Adaptability or versatility
If alert thresholds are made configurable, then user control is improved, but system complexity increases
Solution Approach 1:
The system provides pre-configured alert thresholds and notification preferences that are established in advance. Users can select from predefined sentiment thresholds and notification methods without having to create complex configuration rules from scratch. This preliminary setup reduces the perceived complexity while maintaining adaptability through customizable parameters.
Data Source
AI summary
Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: obtaining textual based message data of a messaging system; processing the textual based message data to determine one or more sentiment parameter associated to the textual based message data; and outputting an alert based on a result of the processing.