Sentiment Analysis System for Group Conversation Content Alignment
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Solution Overview
Problem
Current methods for analyzing sentiment in social media groups are cumbersome and time-consuming, often requiring manual effort to determine group sentiment, which can lead to inaccurate results and conflicts when sharing content, especially in rapidly changing online environments.
Innovation Solution
Implementing a system that uses data mining and machine learning with natural language processing for continuous sentiment analysis, allowing for automatic determination and comparison of content sentiment with group sentiment, enabling real-time decision-making on sharing content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sentiment analysis is performed by checking each message in the group, then the user can understand the group sentiment before sharing content, but the process becomes time-consuming and cumbersome
Solution Approach 1:
The patent replaces the manual mechanical process of reading and rating each message with an automated computational sentiment analysis system. The system automatically analyzes group messages, determines group sentiment, and compares it with the content to be shared, eliminating the need for manual message-by-message review while maintaining or improving analysis accuracy.
Solution Approach 2:
The patent introduces an intermediary sentiment analysis system that acts as a mediator between the user and the group content. This system automatically processes group messages, determines sentiment, and provides guidance to users on whether their content aligns with group sentiment, saving time while preserving accurate sentiment assessment.
2Reliability
If manual sentiment analysis is performed to ensure content aligns with group sentiment, then content conflicts are avoided, but the process is not practical for large amounts of content
Solution Approach 1:
The patent replaces manual sentiment analysis with an automated system that efficiently processes large volumes of group messages and determines sentiment alignment. This computational approach maintains reliable content sentency alignment while dramatically improving productivity by eliminating the need for users to manually review extensive content.
Solution Approach 2:
The system performs self-service sentiment analysis by automatically monitoring group conversations, determining group sentiment, and comparing it with the content to be shared. This eliminates the need for manual intervention while ensuring content aligns with group sentiment, thereby maintaining reliability and improving efficiency.
3Productivity
If content is machine-forwarded automatically, then the sharing process is efficient, but it is not possible to manually check group sentiment
Solution Approach 1:
The patent introduces an intermediary automated sentiment analysis system that bridges the gap between machine forwarding and sentiment checking. This system automatically monitors group sentiment and compares it with the content to be forwarded, enabling efficient automated sharing while ensuring sentiment synchronization through computational analysis rather than manual review.
Solution Approach 2:
The patent replaces manual sentiment checking with an automated computational system that performs sentiment analysis and synchronization. This allows machine-forwarded content to maintain sentiment alignment with the group through automated analysis, preserving both forwarding efficiency and sentiment precision.
4Measurement precision
If users manually review every piece of information in the group to determine sentiment, then accurate sentiment analysis is possible, but the process is problematic and time-consuming
Solution Approach 1:
The patent replaces the complex manual review process with an automated sentiment analysis system that computationally processes group messages. This system maintains accurate sentiment analysis by systematically evaluating content while eliminating the complexity and time requirements of manual message-by-message review and rating.
Data Source
AI summary
The present disclosure provides, among other things, methods and systems of managing communications, the methods and systems including: receiving a first group communication from a first group; determining, based on the first group communication, a first group sentiment; receiving a first communication with a request to send the first communication to the first group; determining, based on the first communication, a first communication sentiment; comparing the first group sentiment with the first communication sentiment; and based on the comparing, performing an action on the request to send the first communication.