Text Analytics for Survey Responses (TASR)
Description
Quickly and accurately pulling significant topics and themes from unstructured text responses to DHS internal surveys.
Detailed example
The systems outputs include a set of topics inferred or surfaced from the raw text comment data, as well as sentiments or other classifications inferred from the data.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
The intended purpose of the AI is to perform topic modeling, sentiment analysis, or other text classification tasks on responses provided to internal staff DHS Pulse Survey questions. Text Analytics for Survey Responses (TASR) is an application for performing Natural Language Processing (NLP) and text analytics on survey responses. It is currently being applied by DHS Office of the Chief Human Capital Officer (OCHCO) to analyze and extract significant topics/themes from unstructured text responses to open-ended questions in the quarterly DHS Pulse Surveys. Results of extracted topics/themes are provided to DHS Leadership to better inform agency-wide efforts to meet employees’ basic needs and improve job satisfaction
Controls / human review
ATO: No; PIA: Not published
Data needed
Pulse survey data.