FeedbackMap: a tool for making sense of open-ended survey responses

Doug Beeferman, Nabeel Gillani
6/26/2023
cs.CL

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Abstract

Analyzing open-ended survey responses is a crucial yet challenging task for social scientists, non-profit organizations, and educational institutions, as they often face the trade-off between obtaining rich data and the burden of reading and coding textual responses. This demo introduces FeedbackMap, a web-based tool that uses natural language processing techniques to facilitate the analysis of open-ended survey responses. FeedbackMap lets researchers generate summaries at multiple levels, identify interesting response examples, and visualize the response space through embeddings. We discuss the importance of examining survey results from multiple perspectives and the potential biases introduced by summarization methods, emphasizing the need for critical evaluation of the representation and omission of respondent voices.

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Cite this paper

@article{beeferman2023feedbackmap,
  title  = {FeedbackMap: a tool for making sense of open-ended survey responses},
  author = {Doug Beeferman and Nabeel Gillani},
  year   = {2023},
  eprint = {2306.15112},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.15112v1}
}

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