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Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Foreword -- Acknowledgments -- Introduction -- 1 What is big data? -- Aims of this book -- Chapter snapshot -- Defining big data -- Big data examples -- Impact of big data on research fields -- Big data and digital life -- Limits and assumptions of big data -- Big data beginnings for qualitative research -- 2 Big data in historical context -- Defining data -- Big science and small science -- Beginning of big textual data -- Big data: Coining and use -- Uses of big textual data today -- Knowledge politics and the history of big data -- 3 Challenges of big data for qualitative researchers -- Challenges of working with big data -- Complexities of data privacy and ownership -- Challenges of big data acquisition -- Challenges of BDA -- 4 Potentials of big data analytics for qualitative researchers -- Text mining -- Opinion mining or sentiment analysis -- Information and data visualization -- Netnography -- Follow-the-thing methods -- Mobile research methods -- Multimodal analysis -- Rythmanalysis -- Conclusion -- 5 Big data ethics, privacy, and dataveillance -- Privacy and dataveillance -- Consent -- Implications -- Conclusion -- 6 Anticipating big data futures for qualitative researchers -- References -- Index.

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.

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.

Amid the big claims of big data, analytics, datification, and data mining, this article answers central questions for qualitative research. In the debates about the enormity and ubiquity of data in the digital world, qualitative research endeavors are seemingly threatened. But is big data necessarily better? Can big data answer the fundamental questions that qualitative researchers ask? This article interrogates the key issues for qualitative researchers in the big data era, positioning big data in its historical context. This article offers a critique of assumptions about access to big data, and uncovers the dark side of big data and privacy in a risk society. The potentials of big data for qualitative research are examined, providing recommendations to bring together complementary research endeavors that map large scale social patterns using big data with qualitative questions about participants' subjective perceptions, rich expression of feelings, and reasons for human action.

"The unprecedented rate of global, technological, and societal change calls for a radical, new understanding of literacy. This book offers a nuanced framework for making sense of literacy by addressing knowledge as contextualized, embodied, multimodal, and digitally mediated. In today's world of technological breakthroughs, social shifts, and rapid changes to the educational landscape, literacy can no longer be understood through established curriculum and static text structures. To prepare teachers, scholars, and researchers for the digital future, the book is organised around three themes-Mind and Materiality; Body and Senses; and Texts and Digital Semiotics-to shape readers' understanding of literacy. Opening up new interdisciplinary themes, Mills, Unsworth, and Scholes confront emerging issues for next-generation digital literacy practices. The volume helps new and established researchers rethink dynamic changes in the materiality of texts and their implications for the mind and body, and features recommendations for educational and professional practice"--

AbstractEducational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational landscape constantly evolves, where tertiary institutions are incorporating new modes of content delivery, hybrid-style learning, and interactive technologies. Investments into digital expansions must be taken with caution, particularly prior to the procurement of technology, with a need for the proposed interventions' scalability, sustainability, and serviceability to be considered. This article presents the Triple-S framework for educators, administrators, and educational institutions, and outlines examples of its application within curricula. The paper synthesises research evidence to provide the foundation underlying the key principles of the Triple-S framework, presenting a useful model to use when evaluating digital interventions. Utilising the framework for decisions regarding the acquisition of educational technology, devices, software, applications, and online resources can assist in the assurance of viable and appropriate investments.
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Research focusing on the management of emotion features prominently in studies of employee attrition, gender inequality and workplace satisfaction, but rarely in research on worker solidarity. Against a backdrop of increasing individualisation within late modern society, research about workplace management of emotion has become bifurcated along sociological or organisational psychology lines. Within the sociology literature, management of emotion is theorised as a commercialised, relational and (often) alienating experience. Within organisational psychology literature and research, the emphasis is on harnessing individual traits and skills (e.g. emotional intelligence) to regulate emotions for increased productivity and employee retention. In this article, the authors call for a new research agenda that prioritises the examination of solidarity between workers alongside the analysis of emotion management. This call is based in a critical reading of the sociological and organisational psychology scholarship addressing the management of emotions. Through the example of teaching work, the authors provide a critique of scholarship on workplace strategies that promote highly individualised understandings of managing emotions through resilience training and other simplified techniques. They argue that workplaces should recognise the dangers of uncritically adopting individualised strategies for managing emotions, and propose a research agenda that seeks to understand how emotion management can affect worker solidarity.