Opinion Search Engine Sentiment Analysis Visualization
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Solution Overview
Problem
Conventional search engines fail to effectively incorporate social media posts and sentiment analysis, lacking the ability to provide human opinions, sentiment trends over time, and user feedback, particularly in the context of online advertisements.
Innovation Solution
A system and method for an opinion search engine that processes and visualizes aggregated social media data using natural language processing and sentiment analysis, incorporating a storm check module, data acquisition, visualization, analytics, and storage modules to provide a visual representation of public opinions and sentiments on entities, products, and locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional search engines return factual data and generic information, then information completeness is improved, but relevance to user sentiment and opinion needs deteriorates
Solution Approach 1:
The patent combines conventional search engine functionality with sentiment analysis capabilities by integrating multiple data sources including social media posts, news articles, and review sites. The system merges factual information retrieval with emotional sentiment detection, allowing simultaneous delivery of both objective data and subjective public opinion in a unified search result presentation.
Solution Approach 2:
The search engine is designed to perform multiple functions simultaneously: retrieving factual information, analyzing sentiment, detecting public opinion trends, and presenting both objective and subjective data. This multi-functional approach allows the system to serve diverse user needs ranging from factual inquiry to sentiment-based decision making within a single platform.
2Adaptability or versatility
If search engines incorporate social media posts and sentiment analysis, then user feedback capability is improved, but system complexity increases
Solution Approach 1:
The system architecture is segmented into distinct functional modules: data acquisition module for collecting social media posts, news articles and reviews; sentiment analysis module for detecting emotional sentiment; opinion aggregation module for synthesizing public opinion; and presentation module for displaying results. This segmentation allows each component to specialize in specific tasks while maintaining overall system manageability through modular design.
Solution Approach 2:
The patent introduces an intermediary layer between raw social media data and search results that performs automated sentiment analysis and opinion aggregation. This intermediary processing layer translates unstructured social media content into structured sentiment metrics, simplifying the integration of user feedback capabilities without directly exposing the complexity of data processing to end users.
3Ease of operation
If conventional search engines provide generic descriptions, then ease of operation is maintained, but measurement precision of public sentiment deteriorates
Solution Approach 1:
The system changes the parameters of search results by introducing sentiment metrics (positive/negative/neutral scores), public opinion aggregates, and sentiment trends alongside traditional factual information. These parameter additions enable precise measurement of public sentiment while maintaining the original search interface, allowing users to access detailed sentiment analysis without complicating the basic search operation.
Data Source
AI summary
Embodiments of the present disclosure are directed to methods, computer program products, computer systems for providing a computing search platform for conducting opinion searches over the Internet concerning aggregated social media electronic messages about public opinions and public sentiments for a wide variety of matrices, such as social media posting of a particular industry over a specified time period, electronic social media posting on the public sentiments, public buzz, and public mood. Methods and systems of the present disclosure are directed to collecting and analyzing unstructured social media messages and correlating with structured entity representations in order to discern amount of interest in (buzz) and feelings about (mood) the real world organizations, people, products, and locations described by those entity representations transforming the data into a readily understandable visual display of the aggregated results on a computer display.