Data Theory. Simon Lindgren

Чтение книги онлайн.

Introduction: Data/Theory

      This book is a tentative and modest proposal on how to think and operate as a theoretically sensitive social scientist in the age of datafication, especially when researching sociality and politics through the internet. The book emphasises the need to think freely and openly about both theory and method, and goes beyond some of the ways of doing social research that are dominant today. It does so by playfully and tentatively combining elements of theories and methods, some of which are commonly seen as being incompatible.

      In the face of the availability of new types of digital research data, and the contemporary popularity of computational methods in an increasing range of scholarly fields, the book should be read as an explorative attempt to make synergetic gains by harnessing the respective powers of interpretive social analysis and computational methods within one and the same research framework. This is not to say that the proposed hybrid approach must replace any other existing approach, but I want to explore potential points of contact between some concepts and strategies that are not regularly combined.

The book is tentative because it does not enter any deeper discussion about the ontological, epistemological, or technical appropriateness of combining, for example, vector models with selectively read parts of Laclau and Mouffe’s discourse analysis, or social media metrics with elements of Bourdieu’s theory of practice. Nor does it address, in any conventional way, the discussions about using ‘quantitative’ scores and measures as input for ‘qualitative’ readings, that its case examples are likely to invite. This conscious choice has been made in order for the argument not to get stuck with such things. The book as a whole should be read as a proposal: ‘What if we did it like this?’ This is a way of exploring how far things can bend.

      Furthermore, the proposal that I make in this book is meant to be modest. A significant amount of valuable and important work has already been done, and continues to be carried out, along the rough lines that I am suggesting, by scholars in fields such as science, technology, and society studies (Marres, 2017), mixed methods research (Hesse-Biber and Griffin, 2013), analytical sociology (Keuschnigg, Lovsjö, and Hedström, 2018), and computational social science (Lazer et al., 2009). In developing my contribution to the discussion of how the data/theory equation can be balanced in contemporary data-driven social research, I draw on influences from all of these areas. In addition, there is a vast literature in the area of the philosophy of science, where I am by no means an expert, but with which the book still sometimes enters into partial dialogue. Therefore, the book should be read for what it is – that is, an account by an alleged ‘qualitative’ sociologist entering the field of computational methods, with the aim of tracing the outlines of a hybrid methodological position potentially to be held, not in particular by data scientists or computational social scientists, nor by digital ethnographers or anthropologists, but by scholars wanting to maintain an interpretative sociological framework for analysis, while incorporating computational methods that follow society’s datafication.

Outline of this book

The first chapter of the book, Beyond Method, is about the need to rethink and repurpose research methods, as well as the role of social theory. I argue that social researchers must move beyond prevailing notions of methodology in order to find new and creative solutions in response to an increasingly complex social reality.

      The second chapter, Decoding Social Forms, turns to the empirical subject area of the book – social media politics СКАЧАТЬ