Thinking about Sources as Data: Reflections on Epistemic Network Analysis as a Technique for Historical Research

Abstract

Network models, in particular social network models, have improved our understanding of a variety of historical phenomena, including correspondence communities, trade networks, citation patterns, dissemination of news, and so on. In many cases, social network analysis has been used to show relationships among people—who corresponded with, traded with, cited, or otherwise interacted with whom? But what if we extended our scope to consider the networks of knowledge created by these individuals? Instead of asking merely “Who was in this network and how were they connected?”, we could ask, “How did information move through this network?” Such questions more closely model the qualitative questions that historians concerned with discourse and concepts have traditionally asked and usually try to answer without computational approaches; however, as access to historical data is expanding rapidly due to digitization efforts, it will be useful, if not necessary, to collaborate with machines on our analyses. To do so, we need to think about mixed-methods approaches that integrate the strengths of humans and computers, and network analysis is one methodological approach that could prove helpful in answering the kinds of qualitative research questions often asked by social, cultural, and intellectual historians.1 In this chapter we reflect on the use of epistemic network analysis (ENA) as a tool for modeling conceptual networks. Because there are a number of resources that explain ENA in great detail as a