Sentiment Vector Injection for Emotional Communication in Messaging
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Solution Overview
Problem
Current electronic communication methods lack the ability to convey subtle emotional cues, leading to misunderstandings and negative impacts on mental and emotional health, and there is a need for personalized, therapeutic digital content delivery and rating systems that account for user consumption habits.
Innovation Solution
A method and system that impose dynamic sentiment vectors on electronic messages based on emotionally-charged language, using AI and machine learning to analyze user input and deliver personalized digital therapeutics, and a system for rating and tracking digital content's psycho-emotional effects for targeted advertisement delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If electronic messaging is used for communication, then instant delivery and limitless distance connectivity are achieved, but emotional cues and subtle communication signals are lost
Solution Approach 1:
The patent introduces an intermediary system that analyzes electronic messages and injects emotional context back into the communication. This mediator processes the digital message, detects emotional content, and reconstructs the emotional dimension that was lost in the digital transition, thereby resolving the contradiction between speed and emotional information preservation.
Solution Approach 2:
The system changes the parameters of electronic communication by adding emotional dimension data to the message stream. It transforms standard text-based communication into emotionally-enriched communication by modifying the message parameters to include sentiment analysis, emotional context, and communicative intent, thereby recovering lost emotional information.
2Adaptability or versatility
If digital content consumption is tracked for therapeutic value, then personalized therapeutic delivery is achieved, but system complexity increases
Solution Approach 1:
The patent implements a self-service system where the digital content automatically tags itself with therapeutic value metadata and the system autonomously tracks consumption patterns. This self-tagging and automatic tracking mechanism reduces the need for complex manual intervention while enabling personalized therapeutic delivery, thereby resolving the contradiction between adaptability and system complexity.
Solution Approach 2:
The system performs preliminary actions by pre-tagging digital content with therapeutic value metadata before delivery. This advance preparation allows the system to quickly match content with user needs without complex real-time analysis, reducing system complexity while maintaining high adaptability for personalized therapeutic delivery.
3Loss of information
If sentiment vectors are imposed on electronic messages, then emotional communication is enhanced, but processing time increases
Solution Approach 1:
The patent applies partial action by selectively analyzing only the portions of messages that contain emotional content rather than processing every message in full detail. This selective approach enhances emotional communication where needed while minimizing processing time for routine communications, thereby resolving the contradiction between emotional information preservation and processing time.
Solution Approach 2:
The system implements periodic action by applying sentiment analysis at specific intervals and only when triggered by certain conditions, rather than continuously analyzing every message. This periodic processing maintains emotional communication enhancement while significantly reducing overall processing time and computational burden.
Data Source
AI summary
The present invention comprises of receiving a text input comprising message content from an electronic computing device associated with a user; parsing the message content comprised in the text input for emotionally-charged language; assigning a sentiment value, based on the emotionally-charged language, from a dynamic sentiment value spectrum to the text input; and, based on the sentiment value, imposing a sentiment vector, corresponding to the assigned sentiment value, to the text input, the imposed sentiment vector rendering a sensory effect on the message content designed to convey a corresponding sentiment.