Qualtrics, LLC

R David Norton

Jamie Morningstar

Zheng Fang

Andrew Carr

This disclosure relates to methods, non-transitory computer readable media, and systems apply machine-learning techniques and computational sentiment analysis to summarize sentences extracted from a group of textual responses or to select representative-textual responses from the group of textual responses. By using a response-extraction-neural network to extract (and sometimes paraphrase) sentences from textual responses, the disclosed methods, non-transitory computer readable media, and systems can generate a response summary of textual responses based on sentiment indicators corresponding to the textual responses. By applying a machine-learning classifier to generate textual quality scores for textual responses, the disclosed methods, non-transitory computer readable media, and systems select representative-textual responses from a group of textual responses based on relevancy parameters and sentiment indicators corresponding to the textual responses. Such computational techniques generate response summaries and representative responses that provide an efficient snapshot of a group of textual responses analyzed by machine learners.

Intelligently summarizing and presenting textual responses with machine learning

This disclosure covers methods, systems, and computer-readable media that identify a topic variance from digital survey responses and provide a variety of functionalities to a digital survey system based on the topic variance (i.e., by modifying a digital survey reporting structure based on the topic variance). In certain embodiments, the disclosed systems analyze one or more sets of digital survey responses to generate one or more response models. Furthermore, the disclosed systems can analyze the one or more response models to identify a topic variance (e.g., an emerging topic, a change in trend for a topic, and/or a change in sentiment for a topic). Upon identifying a topic variance, the disclosed systems modify a digital survey reporting structure and/or generate notifications based on the identified topic variance.

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Orem, UT, United States of America

R David Norton