Redefining Qualitative Analysis in the AI Era: Utilizing ChatGPT for Efficient Thematic Analysis
September 19, 2023 Β· Declared Dead Β· π Computers in Human Behavior
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
He Zhang, Chuhao Wu, Jingyi Xie, Yao Lyu, Jie Cai, John M. Carroll
arXiv ID
2309.10771
Category
cs.HC: Human-Computer Interaction
Citations
121
Venue
Computers in Human Behavior
Last Checked
4 months ago
Abstract
AI tools, particularly large-scale language model (LLM) based applications such as ChatGPT, have the potential to simplify qualitative research. Through semi-structured interviews with seventeen participants, we identified challenges and concerns in integrating ChatGPT into the qualitative analysis process. Collaborating with thirteen qualitative researchers, we developed a framework for designing prompts to enhance the effectiveness of ChatGPT in thematic analysis. Our findings indicate that improving transparency, providing guidance on prompts, and strengthening users' understanding of LLMs' capabilities significantly enhance the users' ability to interact with ChatGPT. We also discovered and revealed the reasons behind researchers' shift in attitude towards ChatGPT from negative to positive. This research not only highlights the importance of well-designed prompts in LLM applications but also offers reflections for qualitative researchers on the perception of AI's role. Finally, we emphasize the potential ethical risks and the impact of constructing AI ethical expectations by researchers, particularly those who are novices, on future research and AI development.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted