Patterns (Jun 2021)
How can big data shape the field of non-religion studies? And why does it matter?
Abstract
Summary: The shift of attention from the decline of organized religion to the rise of post-Christian spiritualities, anti-religious positions, secularity, and religious indifference has coincided with the deconstruction of the binary distinction between “religion” and “non-religion”—initiated by spirituality studies throughout the 1980s and recently resumed by the emerging field of non-religion studies. The current state of cross-national surveys makes it difficult to address the new theoretical concerns due to (1) lack of theoretically relevant variables, (2) lack of longitudinal data to track historical changes in non-religious positions, and (3) difficulties in accessing small and/or hardly reachable sub-populations of religious nones. We explore how user profiling, text analytics, automatic image classification, and various research designs based on the integration of survey methods and big data can address these issues as well as shape non-religion studies, promote its institutionalization, stimulate interdisciplinary cooperation, and improve the understanding of non-religion by redefining current methodological practices. The bigger picture: It is becoming increasingly clear that secularity and non-religion are progressively turning into a relevant component of social life in both western and non-western countries and that they are connected with a variety of pressing issues such as civic engagement, human rights, and social integration. While traditional methodological approaches remain important to understand the varieties of non-religion, Big Data can significantly shape the way in which social scientists frame and analyze the puzzles within this emerging academic field. Nevertheless, large unstructured data collections and classification algorithms remain widely underused in sociology of religion, hindering its potential. We argue that to let Big Data in means to build an interconnected, interdisciplinary, and cooperative field situated at the intersection of non-religion studies and data science.
