Automated Social Media Data Classification for Brand Monitoring
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Solution Overview
Problem
The social web generates a vast volume of data, making it challenging for brands to efficiently identify and respond to relevant social media communications, as traditional listening platforms deliver high volumes of irrelevant results and require costly human intervention for categorization.
Innovation Solution
A computer network system that extracts social media data of interest from multiple platforms, applies semantic text analysis and classification using trained classifiers, and presents relevant social media objects to facilitate timely user action, allowing for targeted customer engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional keyword/Boolean listening platforms are used to monitor social media, then high volumes of posts matching search criteria are delivered, but the results are completely unrelated to the company's brand and require costly human intervention for categorization
Solution Approach 1:
The patent replaces manual human categorization with automated text analytics and classification algorithms. The system uses computational methods to analyze social media posts, extract meaningful information, and categorize them by relevance to the brand, eliminating the need for costly human intervention while maintaining high processing volumes.
Solution Approach 2:
The system changes the parameter of post classification from manual human judgment to automated algorithmic classification. By implementing machine learning models and text analytics, the system transforms unstructured social media data into categorized insights automatically, resolving the contradiction between high volume processing and relevance accuracy.
2Loss of information
If manual human reading and categorization of each social media post is performed, then understanding of post content is achieved, but the process is costly and inefficient, preventing timely response to posts other than those directed to company accounts
Solution Approach 1:
The patent substitutes manual human reading and categorization with automated text analytics systems. The system uses natural language processing, sentiment analysis, and classification algorithms to understand post content automatically, enabling rapid processing of millions of posts while maintaining comprehension quality.
Solution Approach 2:
The system enables self-service automated classification where the text analytics engine independently analyzes and categorizes posts without human intervention. This self-acting system continuously monitors social media streams, extracts relevant information, and prioritizes posts for response based on automated relevance scoring.
3Reliability
If comprehensive monitoring of all social media conversations is attempted, then complete brand reputation management is achieved, but the staggering volume of data makes it challenging to identify relevant communications
Solution Approach 1:
The patent segments the overwhelming volume of social media data into manageable categories using automated classification. The system divides posts into segments based on relevance to the brand, sentiment, topic, and urgency, making the complex data set organized and actionable. This segmentation approach maintains comprehensive monitoring while reducing processing complexity.
Solution Approach 2:
The system introduces text analytics and classification algorithms as intermediary processing layers between raw social media data and brand managers. These intermediaries automatically filter, categorize, and prioritize the staggering volume of conversations, making relevant brand-related communications identifiable without requiring direct human analysis of all data.
4Reliability
If rapid response to viral social media content is implemented, then brand reputation protection is improved, but the volume and pace of social communications make timely identification of relevant posts essential and challenging
Solution Approach 1:
The patent implements preliminary automated classification and prioritization of social media posts before they can go viral. The system continuously pre-processes and categorizes incoming posts, identifying brand-relevant content in advance and preparing it for rapid response. This preliminary action ensures that when viral moments occur, the brand can respond immediately with already-identified relevant posts.
Solution Approach 2:
The system replaces slow manual monitoring with automated real-time text analytics that can process and identify relevant posts instantaneously. The automated classification engine operates at the speed of social media data flow, enabling timely identification of viral content while maintaining brand reputation protection.
Data Source
AI summary
A system and method are provided for targeting customers through social networks. Social media data of interest associated with a plurality of social media objects are extracted from at least one social networking platform. The social media data of interest are stored. The social media data are classified according to pre-defined categories. Based on the classifying, a subset of the plurality of social media objects relevant to a campaign targeting customers is identified. At least one social media object of the subset of social media objects is presented to a user in a form adapted to facilitate user action on the at least one social media object.