Social Data Term Analysis System for Sentiment Detection

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Solution Overview

Problem

Businesses face challenges in effectively monitoring and understanding consumer commentary on social media to identify potential customers and sales leads, as well as addressing customer service issues, due to the vast and unstructured nature of social data.

Innovation Solution

A system and method for performing term analysis on social media data across multiple sources, utilizing semantic analysis and user interfaces to identify significant terms, sentiment, and context, allowing businesses to visualize and interact with the results for informed decision-making.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If businesses monitor social media data across multiple sources, then the quantity of information available increases, but the complexity of processing and analyzing the data increases

Engineering Contradiction:

Improvequantity of social media dataVSAvoidcomplexity of data processing system

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent segments the complex data processing task into distinct functional modules: data collection from multiple sources, data cleaning and preprocessing, term extraction and analysis, sentiment analysis, and result visualization. Each module handles a specific aspect of the analysis, making the overall system more manageable and scalable while processing large volumes of social media data

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If term analysis is performed on large volumes of social data, then the accuracy of understanding consumer sentiment improves, but the time required for analysis increases

Engineering Contradiction:

Improveaccuracy of sentiment understandingVSAvoidanalysis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary data cleaning, normalization, and preprocessing steps before the main term analysis. Stop words are removed, data is standardized, and relevant terms are pre-identified using frequency analysis. This preliminary processing reduces the complexity of subsequent sentiment analysis and enables faster, more accurate results when analyzing large datasets

Inventive Principle:

Principle #10Preliminary action

3Manufacturing precision

If detailed term analysis is conducted to identify actionable content, then the quality of marketing insights improves, but the resource consumption increases

Engineering Contradiction:

Improvequality of marketing insightsVSAvoidcomputational resource consumption

Core Design Contradiction:

Manufacturing precisionVSUse of energy by moving object

Solution Approach 1:

The patent implements a multi-level analysis approach where the system first performs a quick frequency-based term extraction to identify potential keywords, then applies more computationally intensive sentiment analysis only to the most relevant terms and topics. This partial application of detailed analysis to only the most promising data segments maintains high insight quality while significantly reducing overall computational resource consumption

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS9583099B2Method and system for performing term analysis in social data

Publication Date: 2017.02.28 ORACLE INT CORP

AI summary

Disclosed is a system, method, and computer program product for allowing an entity to access social media data, and to perform term analysis upon that data. The approach is capable of accessing data across multiple types of internet-based sources of social data and commentary. A user interface is provided that allows the user to view and interact with the results of performing term analysis.