Comparative Process-Oriented Research Using Social Media and Historical Text

Process-oriented methodologies place a strong emphasis on linking theory with empirical methods. However, in the digital age, this can sometimes be  difficult to do. For example, much of our social lives increasingly occur online and we leave behind an enormous digital footprint. These data can be understood through a variety of empirical methods. The same can be said about the digital archiving of historical data. However, it is all too tempting to study these data without a clear theoretical framework. This paper seeks to understand partiality and perspectivity within comparative, historical technologically-mediated empirical methods. This paper uses two empirical data sources: one contemporary (Twitter) and the other, historical (Google Books 'n-gram' data) to make an argument that we can use process-oriented theory to conduct empirical research. Additionally, it argues that process-oriented perspectives help bring notions of figuration into data-driven research, which enables sociologists to also see and locate their own figuration. Canonical process-oriented researchers such as Norbert Elias used mixed methods approaches, including visual maps and quantitative surveys. He also used standardized data. This paper argues that quantitative methods are important to process-oriented methodologies and can be successfully used to identify a figuration. Specifically, Social Network Analysis (SNA) does this. This paper uses SNA to visually reveal sub-groups within a figuration using both Twitter data and Google n-gram data. Like Elias, this paper examines historical sources and life documents. However, it extends these to Big Data empirical sources and argues that, for example,tweets can be understood as 'life documents'. Additionally, methods, such as SNA provide important modes to see how a figuration develops over time.