2024
ACL
ACL 2024
Automating Qualitative Data Analysis with Large Language Models
Abstract
AbstractThis PhD proposal aims to investigate ways of automating qualitative data analysis, specifically the thematic coding of texts. Despite existing methods vastly covered in literature, they mainly use Topic Modeling and other quantitative approaches which are far from resembling a human’s analysis outcome. This proposal examines the limitations of current research in the field. It proposes a novel methodology based on Large Language Models to tackle automated coding and make it as close as possible to the results of human researchers. This paper covers studies already done in this field and their limitations, existing software, the problem of duplicating the researcher bias, and the proposed methodology.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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Keyword Pioneer
— qualitative data analysis
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Natural Language Processing > Generation > Text Generation
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Resources & Methods > Large Language Models
Artificial Intelligence > Core AI > Large Language Models
Machine Learning > Learning Paradigms > Zero-Shot Learning