Using machine learning to generate segments from unstructured text and identify sentiments for each segment

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a computer system to:

• receive user feedback data comprising unstructured text;
• identify, using a segmentation machine learning model, a plurality of segments from the unstructured text, wherein a given segment of the plurality of segments comprises a salient portion of the unstructured text;
• and
• generate, using a sentiment identifying machine learning model, a sentiment label for each segment of the plurality of segments.

A system comprising:

• at least one processor;
• and
• at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
• receive user feedback data comprising unstructured text;
• identify, using a segmentation machine learning model, a plurality of segments from the unstructured text, wherein a given segment of the plurality of segments comprises a salient portion of the unstructured text;
• and
• generate, using a sentiment identifying machine learning model, a sentiment label for each segment of the plurality of segments.