Qualitative Data Analysis (QDA) is a subjective form of text analysis where non-structured textual data, including interview transcripts, social media text, photographs, audio or video files, or almost any other information is closely examined to identify topics, narratives, structures, or themes. QDA can be done manually, on paper, but is typically performed with the help of software tools. If you are new to the technique, be sure to check out the theory guides on the left before diving into the software!
Related Techniques: Text Analysis, Social Media Analysis
This technique is part of the Analysis activity
The Coding Manual for Qualitative Researchers by
The Coding Manual for Qualitative Researchers is unique in providing, in one volume, an in-depth guide to each of the multiple approaches available for coding qualitative data. In total, 29 different approaches to coding are covered, ranging in complexity from beginner to advanced level and covering the full range of types of qualitative data from interview transcripts to field notes. For each approach profiled, Johnny Saldaña discusses the method’s origins in the professional literature, a description of the method, recommendations for practical applications, and a clearly illustrated example.
Qualitative Data Analysis by
The latest edition of this best-selling textbook by Miles and Huberman not only is considerably expanded in content, but is now available in paperback. Bringing the art of qualitative analysis up-to-date, this edition adds hundreds of new techniques, ideas and references developed in the past decade. The increase in the use of computers in qualitative analysis is also reflected in this volume. There is an extensive appendix on criteria to choose from among the currently available analysis packages. Through examples from a host of social science and professional disciplines, Qualitative Data Analysis remains the most comprehensive and complete treatment of this topic currently available to scholars and applied researchers.
Data Mining for the Social Sciences by
We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.
Qualitative Data Analysis with NVivo by
Engaging and accessible, this book offers students a complete guide to using NVivo for qualitative data analysis. Drawing on their wealth of expertise, the authors offer detailed, practical advice that relates to students' own experience and research projects. Packed with real-world examples and case studies, the book supports students through every stage of qualitative data analysis. The Third Edition: Contains fully integrated instructions for using NVivo on both Mac and PC, with screenshots and click-by-click guidance. Seamlessly interweaves theory and practice in easy-to-follow steps. Empowers students to develop their critical thinking. Accompanied by video tutorials for both Mac and PC, web links and a host of other helpful online resources, this step-by-step book removes students′ anxiety about tackling data analysis. Whether for advanced researchers or those approaching the task for the first time, this clear, yet comprehensive guide is the perfect companion for anyone doing qualitative data analysis with NVivo.
The SAGE Handbook of Qualitative Data Analysis by
The wide range of approaches to data analysis in qualitative research can seem daunting even for experienced researchers. This handbook is the first to provide a state-of-the art overview of the whole field of QDA; from general analytic strategies used in qualitative research, to approaches specific to particular types of qualitative data, including talk, text, sounds, images and virtual data. The handbook includes chapters on traditional analytic strategies such as grounded theory, content analysis, hermeneutics, phenomenology and narrative analysis, as well as coverage of newer trends like mixed methods, reanalysis and meta-analysis. Practical aspects such as sampling, transcription, working collaboratively, writing and implementation are given close attention, as are theory and theorization, reflexivity, and ethics. Written by a team of experts in qualitative research from around the world, this handbook is an essential compendium for all qualitative researchers and students across the social sciences.
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