Ensuring Quality: The Power and Potential of Naturally Occurring Data in the Social Sciences

This chapter overviews the principles and practices for ensuring the quality of social scientific research using naturally occurring data to study social interaction. Excavating their initial use as empirical evidence by conversation analysts in the 1960s, we show how the choice to examine naturally occurring data was fuelled by concerns with analytic transparency and integrity (Sacks, 1984). Over time, the centrality of quality management within approaches that rely on naturally occurring data, such as conversation analysis, discursive psychology, ethnomethodology, and membership categorisation analysis, led to the development of quality-insuring methodological practices and principles that inform every step of the research process (Peräkylä, 2011). We spend most of the chapter discussing these practices and principles at four stages of a research project using naturally occurring data: (1) formulating research questions and sourcing naturally occurring data, (2) storing and preparing naturally occurring data for analysis, (3) building collections and analysing naturally occurring data, and (4) publishing research using naturally occurring data. We end the chapter by reflecting on how expanding the scope of research using naturally occurring data provides for new challenges and opportunities for quality insurance.