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Thematic analysis (TA) has been widely used for analyzing qualitative data in many disciplines and fields.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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A coefficient of agreement for nominal scales
Jacob Cohen. 1960 · 1960
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Verbs semantics and lexical selection
Zhibiao Wu and Martha Palmer. 1994 · 1994
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Using thematic analysis in psychology
Virginia Braun and Victoria Clarke. 2006 · 2006
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Agreement and information in the reliability of coding
Klaus Krippendorff. 2011 · 2011
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Five ways of doing qualitative analysis: Phenomenological psychology, grounded theory, discourse analysis, narrative research, and intuitive inquiry
Frederick Joseph Wertz. 2011 · 2011
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Thematic analysis
Virginia Braun and Victoria Clarke. 2012 · 2012
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Theme development in qualitative content analysis and thematic analysis
Mojtaba Vaismoradi, Jacqueline Jones, Hannele Turunen, and Sherrill Snelgrove. 2016 · 2016
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Augmenting qualitative text analysis with natural language processing: methodological study
Timothy C Guetterman, Tammy Chang, Melissa DeJonckheere, Tanmay Basu, Elizabeth Scruggs, and VG Vinod Vydiswaran. 2018 · 2018
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A practical guide to collaborative qualitative data analysis
K Andrew R Richards and Michael A Hemphill. 2018 · 2018
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Can large language models transform computational social science?
Caleb Ziems, William Held, Omar Shaikh, Jiaao Chen, Zhehao Zhang, and Diyi Yang. 2023 · 2018
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Reflecting on reflexive thematic analysis
Virginia Braun and Victoria Clarke. 2019 · 2019
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Natural language processing (nlp) in qualitative public health research: a proof of concept study
William Leeson, Adam Resnick, Daniel Alexander, and John Rovers. 2019 · 2019
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Deep sentiment classification and topic discovery on novel coronavirus or covid-19 online discussions: Nlp using lstm recurrent neural network approach
Hamed Jelodar, Yongli Wang, Rita Orji, and Shucheng Huang. 2020 · 2020
Cited alongside, same era.
Cody: An interactive machine learning system for qualitative coding
Tim Rietz, Peyman Toreini, and Alexander Maedche. 2020 · 2020
Cited alongside, same era.
Do the shuffle: Exploring reasons for music listening through shuffled play
Katie Rose M Sanfilippo, Neta Spiro, Miguel Molina-Solana, and Alexandra Lamont. 2020 · 2020
Cited alongside, same era.
Supporting serendipity: Opportunities and challenges for human-ai collaboration in qualitative analysis
Jialun Aaron Jiang, Kandrea Wade, Casey Fiesler, and Jed R Brubaker. 2021 · 2021
Cited alongside, same era.
Health, psychosocial, and social issues emanating from the covid-19 pandemic based on social media comments: Text mining and thematic analysis approach
Oladapo Oyebode, Chinenye Ndulue, Ashfaq Adib, Dinesh Mulchandani, Banuchitra Suruliraj, Fidelia Anulika Orji, Christine T Chambers, Sandra Meier, and Rita Orji. 2021 · 2021
Challenging big-bench tasks and whether chain-of-thought can solve them
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, and Jason Wei. 2022 · 2022
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Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, and Quoc Le. 2022 · 2022
Later among the works it cites.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed H. Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.
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Cited alongside, same era.
Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2022 · 2022
Cited alongside, same era.
What can transformers learn in-context? a case study of simple function classes
Shivam Garg, Dimitris Tsipras, Percy S Liang, and Gregory Valiant. 2022 · 2022
Cited alongside, same era.
The computational thematic analysis toolkit
Robert P Gauthier and James R Wallace. 2022 · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al. 2022 · 2022
Cited alongside, same era.
Why users (don’t) use password managers at a large educational institution
Peter Mayer, Collins W. Munyendo, Michelle L. Mazurek, and Adam J. Aviv. 2022 · 2022
Cited alongside, same era.
Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
Cited alongside, same era.
Falcon-40B: an open large language model with state-of-the-art performance
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Merouane Debbah, Etienne Goffinet, Daniel Heslow, Julien Launay, Quentin Malartic, Badreddine Noune, Baptiste Pannier, and Guilherme Penedo. 2023 · 2023
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Can large language models be an alternative to human evaluations?
Cheng-Han Chiang and Hung-yi Lee. 2023 · 2023
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Collabcoder: A gpt-powered workflow for collaborative qualitative analysis
Jie Gao, Yuchen Guo, Gionnieve Lim, Tianqin Zhang, Zheng Zhang, Toby Jia-Jun Li, and Simon Tangi Perrault. 2023 · 2023
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Patat: Human-ai collaborative qualitative coding with explainable interactive rule synthesis
Simret Araya Gebreegziabher, Zheng Zhang, Xiaohang Tang, Yihao Meng, Elena L Glassman, and Toby Jia-Jun Li. 2023 · 2023
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Chatgpt outperforms crowd-workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023
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Stefano De Paoli. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Supporting qualitative analysis with large language models: Combining codebook with GPT-3 for deductive coding
Ziang Xiao, Xingdi Yuan, Q. Vera Liao, Rania Abdelghani, and Pierre-Yves Oudeyer. 2023 · 2023
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ReAct: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023 · 2023
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