Big Data for Qualitative Research covers everything small data researchers need to know about big data, from the potentials of big data analytics to its methodological and ethical challenges. The data that we generate in everyday life is now digitally mediated, stored, and analyzed by web sites, companies, institutions, and governments. Big data is large volume, rapidly generated, digitally encoded information that is often related to other networked data, and can provide valuable evidence for study of phenomena. This book explores the potentials of qualitative methods and analysis for big data, including text mining, sentiment analysis, information and data visualization, netnography, follow-the-thing methods, mobile research methods, multimodal analysis, and rhythmanalysis. It debates new concerns about ethics, privacy, and dataveillance for big data qualitative researchers. This book is essential reading for those who do qualitative and mixed methods research, and are curious, excited, or even skeptical about big data and what it means for future research. Now is the time for researchers to understand, debate, and envisage the new possibilities and challenges of the rapidly developing and dynamic field of big data from the vantage point of the qualitative researcher.

Thick Big Data presents the available arsenal of new methods and tools for studying society both quantitatively and qualitatively, opening ground for the social sciences to take the lead in analysing digital behaviour. These tools are critical for students and researchers in the social sciences to successfully build mixed-methods approaches.

Big Data in Psychological Research provides an overview of big data theory, research design and analysis, collection methods, applications, ethical concerns, best practices, and future research directions for psychologists.

′I find your straightforward writing style an absolute joy, such a breath of fresh air!′ - Angie Ash, PhD student ′...thank you very much for your accessible language, clear lay out and practical applied approach. I suspect that this book will never be far from my side over the next 4 years!!′ - Mayen Konarski, PhD student Using straight-forward language Doing Qualitative Research Using Your Computer walks readers through the process of managing and streamlining research projects using commonly available Microsoft software applications. Drawing on a wide range of examples to demonstrate how easy it is to use such software, this guide is full of useful hints and tips on how to manage research more efficiently and effectively, including: - Formatting transcripts for maximum coding efficiency in Microsoft Word - Using features of Word to organize the analysis of data and to facilitate efficient qualitative coding - Synchronizing codes, categories, and important concepts between Microsoft Word and Microsoft Access - Efficiently storing and analyzing the qualitative data in Microsoft Excel - Creating flexible analytic memos in Access that help lead the researcher to final conclusions Ideal for those students or researchers who don′t want to invest in expensive specialised software packages, this guide will be an invaluable companion for anyone embarking on their own research project.

This upper-level textbook presents a new approach to large scale qualitative analysis – the pioneering breadth-and-depth method. It covers the strengths and deployment of “big qual” as a distinct research methodology. The book will appeal to students and researchers across disciplines and methodological backgrounds. The growing availability of large qualitative data sets presents exciting opportunities. Pooling multiple qualitative data sets enhances the possibility of theoretical generalisability and strengthens claims from qualitative research about understanding how social processes work. Given the evolving possibilities that big data offers the humanities and social sciences, this book will be a must-have resource, building capacity and provoking new ways of thinking about qualitative research and its analysis.

Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a means and an object of research, with essays from prominent and emerging scholars such as Rob Kitchin, Renee Sieber, and Mark Graham. Part 1 explores how the advent of geoweb technologies and big data sets has influenced some of geography's major subdisciplines: urban politics and political economy, human-environment interactions, and geographic information sciences. Part 2 addresses how the geographic study of big data has implications for other disciplinary fields, notably the digital humanities and the study of social justice. The volume concludes with theoretical applications of the geoweb and big data as they pertain to society as a whole, examining the ways in which user-generated data come into the world and are complicit in its unfolding. The contributors raise caution regarding the use of spatial big data, citing issues of accuracy, surveillance, and privacy.

This book explores the big data evolution by interrogating the notion that big data is a disruptive innovation that appears to be challenging existing epistemologies in the humanities and social sciences. Exploring various (controversial) facets of big data such as ethics, data power, and data justice, the book attempts to clarify the trajectory of the epistemology of (big) data-driven science in the humanities and social sciences.