Sentiment Analyzer for Electronic Message Composition
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Solution Overview
Problem
Current electronic messaging systems fail to analyze and adjust the sentiment of outgoing messages, leading to potential miscommunication, especially for non-native speakers who struggle to convey intended emotions and meanings.
Innovation Solution
A computing system that analyzes the sentiment of electronic messages in real-time, providing users with options to modify the message layout and word choices to ensure the intended sentiment is conveyed, using a sentiment analyzer to determine and adjust the sentiment score and layout type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a user writes an electronic message in their non-native language, then the message can be sent quickly, but the sentiment and intended meaning may be miscommunicated
Solution Approach 1:
The system provides real-time feedback by analyzing the sentiment of the written message and comparing it with the user's intended sentiment. When a mismatch is detected, the system returns suggestions for alternative wordings to help the user adjust the message to convey the correct sentiment, thereby improving reliability without sacrificing productivity
Solution Approach 2:
The sentiment analyzer acts as an intermediary between the user's intended meaning and the actual message content. It automatically detects sentiment mismatches and provides corrective suggestions, serving as a mediator that helps non-native speakers convey their intended sentiment accurately without requiring them to manually proofread or rewrite the entire message
2Reliability
If the system provides real-time sentiment analysis and suggestions, then sentiment accuracy is improved, but the complexity of the messaging system increases
Solution Approach 1:
The system performs sentiment analysis automatically without requiring user intervention or configuration. The sentiment analyzer independently evaluates the message, detects mismatches between intended and actual sentiment, and generates suggestions autonomously, thereby improving sentiment accuracy while maintaining simple user interaction and avoiding additional system complexity
Data Source
AI summary
Systems, methods and apparatus for authoring an electronic message. In one example, the system, method, and apparatus include receiving an electronic message; categorizing the electronic message based on a message layout type associated with the electronic message; determining, with a sentiment analyzer, a sentiment type and a sentiment score associated with the electronic message; identifying a first plurality of words in the electronic message associated with the sentiment type; and outputting one or more selected from the group consisting of the message layout type, the sentiment type, and the sentiment score associated with the electronic message.