Sentiment Analysis System with Sarcasm Detection for Privacy
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Solution Overview
Problem
Current systems for generating social connections lack the ability to collect and interpret information without limitations while respecting individual privacy rights, particularly in creating and managing transitory sentiment communities based on user emotions from posted content.
Innovation Solution
A server-based system that processes data from multiple sources using a linguistic framework to identify sentiment classifications and intensity ratings, with a sarcasm detection module that modifies sentiment ratings based on a likelihood threshold, generating a transitory sentiment community that ebbs and flows according to defined threshold parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is collected from multiple data sources to create comprehensive sentiment communities, then the quantity and quality of information increases, but privacy rights of individuals may be compromised
Solution Approach 1:
The patent extracts only the necessary sentiment-relevant information from multiple data sources while leaving out personally identifiable information. The system processes data to extract sentiment classifications and intensity ratings without collecting or storing information that would violate privacy rights, thus achieving information completeness for sentiment analysis while protecting individual privacy.
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between raw data collection and final sentiment community generation. This intermediary layer filters and processes data to extract sentiment information while removing or anonymizing personally identifiable information, thereby enabling comprehensive information collection without direct privacy violation.
2Productivity
If sentiment analysis is performed on posted content to identify user emotions, then personalized interactions and product promotion effectiveness improve, but system complexity increases
Solution Approach 1:
The patent segments the sentiment analysis system into distinct functional modules: a sentiment analysis module that processes posted content to identify user emotions, and a community generation module that uses this sentiment information to create transitory sentiment communities. This segmentation allows the system to achieve personalized interaction effectiveness while managing complexity through modular design, where each module has a specific function.
Solution Approach 2:
The patent creates a multi-functional system where the sentiment analysis module serves multiple purposes: identifying user emotions for personalized interactions, determining product promotion effectiveness, and generating transitory sentiment communities. This universality improves productivity by using a single system for multiple functions while avoiding the need for separate complex systems for each function.
3Speed
If transitory sentiment communities are generated in real-time based on user emotions, then responsiveness and personalization improve, but computational resources and processing time increase
Solution Approach 1:
The patent implements dynamic transitory sentiment communities that are continuously created and dissolved based on real-time user sentiment changes. The system dynamically adjusts community composition as users post new content, with communities forming when sentiment thresholds are met and dissolving when they are no longer met. This dynamic approach enables real-time responsiveness while optimizing computational resources by only processing and maintaining communities that currently meet the defined criteria.
Solution Approach 2:
The patent uses parameter changes in sentiment intensity ratings to trigger community formation and dissolution. Instead of continuously processing all user data, the system monitors sentiment parameters and only performs computationally intensive community generation operations when sentiment parameters cross defined thresholds. This approach enables real-time responsiveness while reducing overall computational resource consumption by processing only when necessary.
Data Source
AI summary
A method and system of generating a transitory sentiment community. The method comprises receiving data in a database memory of a server computing device, the data extracted from a plurality of data sources, pre-processing the data based on text character removal and text character replacement, to provide pre-processed data that includes keywords used in a descriptive manner, performing a sentiment analysis on the keywords based at least in part upon a training model, the sentiment analysis identifying a conformance to at least one of a set of sentiment classifications recognized by the training model, and a sentiment intensity rating associated with the conformance, modifying the sentiment intensity rating associated with the sentiment classification upon detecting a sarcasm sentiment above a sarcasm sentiment threshold, and generating the transitory sentiment community based at least in part on the sentiment classification and the modified sentiment intensity rating.