Negative Sentiment Routing for Actionable Social Media Messages
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Solution Overview
Problem
Organizations face inefficiencies in handling long social media messages with negative sentiment, as they are difficult to process due to their length and complexity, often requiring manual analysis to identify actionable content, which can lead to delayed responses and increased customer dissatisfaction.
Innovation Solution
A method and system for determining agent routing in a contact center that involves receiving long social media messages, identifying negative sentiment, determining actionable content, parsing, sorting, and ordering it based on sentiment, information density, and intent, to efficiently route messages to agents for response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis is used to identify actionable content in long social media messages, then measurement precision can be maintained, but productivity decreases and loss of time increases
Solution Approach 1:
The patent segments long social media messages into smaller units (sentences, phrases, or content blocks) that can be independently analyzed by automated text processing techniques. This segmentation enables the system to apply natural language processing algorithms to each segment, maintaining identification accuracy while significantly improving processing throughput compared to manual analysis of entire long messages.
Solution Approach 2:
The patent introduces automated text processing techniques and natural language processing algorithms as intermediaries between the raw social media messages and the final actionable content identification. These intermediary systems automatically analyze message content, detect sentiment, and identify actionable items, thereby maintaining precision while eliminating the time constraints of manual analysis.
2Productivity
If automated text processing is used to identify negative sentiment, then productivity increases, but measurement precision may deteriorate
Solution Approach 1:
The patent applies preliminary text processing steps such as tokenization, stop-word removal, and sentiment lexicon preparation before performing actual sentiment analysis. These preliminary actions pre-process the data to enhance the accuracy of subsequent automated sentiment detection, ensuring that high-speed processing does not compromise identification precision.
Solution Approach 2:
The system incorporates feedback mechanisms where automated sentiment analysis results are continuously refined based on performance metrics and validation against known patterns. This feedback loop allows the automated processing system to learn from its outputs and improve accuracy over time, maintaining measurement precision while preserving the productivity benefits of automation.
3Reliability
If all long social media messages are routed to agents, then reliability of customer service is improved, but loss of time for agents increases and productivity decreases
Solution Approach 1:
The patent extracts and identifies only the actionable content within long social media messages using automated text processing and natural language analysis. By taking out only the relevant actionable items rather than routing entire long messages to agents, the system maintains reliable customer service coverage for all messages while significantly reducing the time agents need to spend on each message by focusing only on actionable portions.
Solution Approach 2:
The patent applies local quality analysis by differentiating between actionable and non-actionable portions of messages. Instead of treating all messages uniformly, the system identifies specific segments requiring agent attention and routes only those portions, thereby maintaining comprehensive service reliability while minimizing agent time investment in proportion to the actual work required.
4Measurement precision
If manual review of long messages is performed, then measurement precision of actionable content is maintained, but device complexity and ease of operation worsen
Solution Approach 1:
The patent replaces manual mechanical review processes with automated text processing systems and natural language processing algorithms. This substitution maintains measurement precision in detecting actionable content while reducing system complexity by eliminating the need for complex manual review workflows, multiple approval layers, and extensive human coordination that would otherwise be required to achieve similar accuracy.
Data Source
AI summary
A contact center system can receive messages from social media sites or centers. The system can review long messages by identifying content in the long message with negative sentiment. The content with negative sentiment is further analyzed to determine whether the identified content is actionable. If the identified content is actionable, the communication system can automatically routed the long message to an agent for response.