gpt_qualitative_analysis
GPT_qualitative_analysis
Science Score: 57.0%
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○Scientific vocabulary similarity
Low similarity (4.9%) to scientific vocabulary
Repository
GPT_qualitative_analysis
Basic Info
- Host: GitHub
- Owner: rishika-bose
- Language: HTML
- Default Branch: main
- Size: 693 KB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Qualitative Coding with GPT-3 and -4
Qualitative analysis of text data, such as from interviews or surveys, requires the analyst to go through the texts, find recurring themes, and match each text to the themes (or ‘codes’) one-by-one [1]. Automating this last step could save researchers significant resources. Large language models such as GPT-3 have allowed the automation of many tasks previously dependent on humans, such as chatting with customers, building web applications, and summarising complex text [2-4]; it may be worth investigating whether they could also be used to automate qualitative coding.
I have used GPT-3 and GPT-4 to code a dataset of free-text responses that was previously coded by experts (from Cabrera et al., 2014 - https://doi.org/10.1007/s12152-014-9223-2). I have then compared the results from the various prompts against each other and against the experts.
This is a project for COGS 402 (https://cogsys.ubc.ca/course-pages/cogs-402/), carried out under the supervision of Dr. Peter Reiner and Imre Bard.
Owner
- Name: Rishika Bose
- Login: rishika-bose
- Kind: user
- Repositories: 1
- Profile: https://github.com/rishika-bose
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Bose" given-names: "Rishika" orcid: "https://orcid.org/0000-0002-3920-3054" title: "GPT_qualitative_analysis" version: 1.0.0 doi: 10.5281/zenodo.1234 date-released: 2023-04-21 url: "https://github.com/rishika-bose/GPT_qualitative_analysis"