ChatGPT for semantic and emotional data

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monitoring the corresponding text input channels and behavioral data (for example, order information entry in the App, frequency of phone inquiries, system messages, etc.), the summary is submitted to analysis. When ChatGPT returns the corresponding emotional results , the operation system receives relevant results and displays them on the corresponding work order in the form of emotion labels. Implement it into specific products to achieve results, as shown in the renderings. A new emotion identifier has been


added to the existing single work order management interface to Afghanistan WhatsApp Number provide real-time feedback on the user's emotion and urgency associated with the work order. When users provide feedback on monitored communication channels, such as messages and emails, the back-end sentiment analysis mechanism will be triggered, and the user information is sent to ChatGPT for semantic sentiment analysis. Through different emoticons and font color combinations, you can convey the most intuitive information to customer service staff. In addition, based on the real-





time emotional information, matching the timeline, a corresponding emotional journey map was also built to comprehensively display the changes in emotions related to the work order, allowing CSR to make a better evaluation from a "perceptual" perspective. In addition to real-time emotion display on the work order management interface, when the mouse hovers over the corresponding icon, the changes in the user's emotion icons in chronological order are connected in series to form a user emotion journey map. Operations staff can take service