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100 1 _aGarcia Quevedo, Diana.
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245 1 0 _aAI for Qualitative Research
_h[electronic resource] :
_bA Hands-On Guide for Management Scholars /
_cby Diana Garcia Quevedo, Josue Kuri.
250 _a1st ed. 2026.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Palgrave Macmillan,
_c2026.
300 _aXII, 174 p. 16 illus., 7 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
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338 _aonline resource
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341 0 _bPDF/UA-1
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341 0 _bTable of contents navigation
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341 0 _bSingle logical reading order
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341 0 _bShort alternative textual descriptions
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341 0 _bUse of color is not sole means of conveying information
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341 0 _bUse of high contrast between text and background color
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505 0 _aChapter 1 Introduction -- Chapter 2 Overview of Artificial Intelligence, Machine Learning, Natural Language Processing, and Large Language Models -- Chapter 3 Natural Language Processing in Management Research -- Chapter 4 Ethical Considerations -- Chapter 5 Systems and Tools to Use NLP and LLMs: Getting Started -- Chapter 6 Using LLMs in Qualitative Analysis -- Chapter 7 Data Evaluation and Validation -- Chapter 8 Classification -- Chapter 9 Clustering and Topic Modeling -- Chapter 10 Information Retrieval (IR) and Retrieval-Augmented Generation (RAG) -- Chapter 11 Perspectives on LLMs in Management and Qualitative Research.
506 0 _aOpen Access
520 _aThis open access book will guide qualitative researchers in the social sciences with little to no coding experience in leveraging large language models (LLMs). Responding to a lack of instructional materials that recognize the need to equip qualitative researchers with the most advanced tools, this book offers a research-focused guide to harness the power of LLMs. The content is divided into two parts, beginning with an introduction to LLMs, natural language processing, and machine learning, as well as a historical and ethical perspective on the use of AI in research. The second part of the book serves as a hands-on guide, providing step-by-step instructions for the use of LLMs to analyze large datasets. It is written with practical cases, taken from management sciences, and emphasizes maintaining a close connection to the data throughout the process. It will be highly valuable to researchers in management studies, as well as in the wider social sciences. Diana Garcia Quevedo is a Visiting Professor at Clemson University, South Carolina, US, and a recipient of the Stand Up for Science fund at ESCP Business School, where she studies innovation in entrepreneurship and green venturing. Her research focuses on the impact of women entrepreneurs on the economy and society. She also works on new methods for qualitative research, particularly large language models, to analyze large amounts of online data inductively. Josue Kuri is a Principal Scientist at Amazon Web Services (AWS), where he leads cloud infrastructure planning automation efforts. At AWS, he pioneered the use of machine learning for network forecasting and the development of a digital twin platform to optimize large-scale digital infrastructure. Prior to AWS, he worked at Google and Facebook (now Meta) on the operational and strategic planning of network infrastructure, including investments in submarine cables. Additionally, he pursues an interest in expanding the use of AI in research and education.
532 8 _aAccessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub.
532 8 _aNo reading system accessibility options actively disabled
532 8 _aPublisher contact for further accessibility information: accessibilitysupport@springernature.com
650 0 _aExecutives
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650 0 _aTechnological innovations.
650 1 4 _aManagement Education.
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650 2 4 _aInnovation and Technology Management.
700 1 _aKuri, Josue.
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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856 4 0 _uhttps://doi.org/10.1007/978-3-032-08872-7
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