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Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Karine Pepin (2CV Research)
An enormous amount of time and resources are devoted to improving data quality in survey research.
The quality of open-ended responses has become a critical factor for researchers in evaluating the validity of each participant. Reading through open-ended responses is a time-consuming task that has been difficult to automate.
While most tools are capable of identifying obviously inappropriate responses such as gibberish and profanity, they generally lack the ability to effectively assess the quality of the content.
With its ability to understand context and user-friendliness, Generative AI opens up opportunities for researchers to automate this laborious cleaning process.
During this session, you will be presented with a practical use case demonstrating how GPT was utilized to efficiently clean open-ended responses on a large scale.
