Using fuzzy coding with qualitative data: example with subjective data in human-computer interaction

Loslever, P.; Gonçalves, Taísa Guidini; Oliveira, Káthia Marçal de; Kolski, Christophe

doi:10.1080/1463922x.2019.1574932

Cited by 3 publications

(1 citation statement)

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“…Annotation style. Finally, since coding is meant to cultivate a particular researcher's understanding of a corpus, no two coders will have the same annotation style (Loslever et al, 2019). Thus, previous efforts to homogenize code annotations, for instance by grouping similar codes from different coders together, should be avoided.…”

Section: Properties Of Qualitative Codingmentioning

confidence: 99%

Qualitative Code Suggestion: A Human-Centric Approach to Qualitative Coding

Piano,

Rahimi,

Cheung

2023

Findings of the Association for Computational Linguistics: EMNLP 2023

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Qualitative coding is a content analysis method in which researchers read through a text corpus and assign descriptive labels or qualitative codes to passages. It is an arduous and manual process which human-computer interaction studies have shown could greatly benefit from NLP techniques to assist qualitative coders. Yet, previous attempts at leveraging language technologies have set up qualitative coding as a fully automatable classification problem. In this work, we take a more assistive approach by defining the task of qualitative code suggestion (QCS) in which a ranked list of previously assigned qualitative codes is suggested from an identified passage. In addition to being usermotivated, QCS integrates previously ignored properties of qualitative coding such as the sequence in which passages are annotated, the importance of rare codes and the differences in annotation styles between coders. We investigate the QCS task by releasing the first publicly available qualitative coding dataset, CVDQuoding, consisting of interviews conducted with women at risk of cardiovascular disease. In addition, we conduct a human evaluation which shows that our systems consistently make relevant code suggestions.

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Section: Properties Of Qualitative Codingmentioning

confidence: 99%