Networks in History
Networks are everywhere. Of course, today we are used to social networks, where information, ideas, and cat memes can spread at an extremely rapid rate. Social scientists call these “network effects”. If I send a meme to two friends, and they send that meme to two friends, and so on, my idea gets to thousands (or more) people with little effort on my part. Social networks amplify this process by creating a bunch of key nodes. If Justin Bieber (113 million followers) retweets the link to my Broadstreet post, our servers might crash.
But this isn’t a post about social networks. It is a post about networks in history. Much like today, networks in history were everywhere. Although our ancestors did not have the technology to make information spread quite as quickly as we do today, historical networks were still mightily important for all sorts of economic, social, and political processes.
We need to look no further than the most recent Broadstreet post for an excellent example. In his first post (a great read!), Yuhua Wang shows how different types of linkages between rulers and local social groups (clans, tribes, ethnic groups) determines just how much national policy aligns with the interests of the broader population.
There are many other questions in historical political economy that could not be answered without considering the structure of networks. For instance, how do we understand inter-regional trade—and its long-run consequences—if we do not have a good idea about trade networks linking cities and people? How do social and political revolutions use transport networks to spread among the population? How can we understand revolutions or social movements without knowing something about how radical ideas spread? Can we fully grasp medieval high politics without having some idea of the various elite networks created via marriage (see below)?
Types of Networks
There are different types of networks that social scientists study. Among the most common are spatial networks. These are networks that link different “nodes” over space. They can be used to answer many questions. For instance, my Broadstreet colleague Adam Slez recently had a great, informative post about how networks can be used to reconstruct “stable geography” when boundaries change (as they so often do!). It is a fascinating use of network analysis.
It is often possible to recreate historical spatial networks because spatial networks leave historical residues. We might be able to find linkages in trade networks via letters between merchants, foreign coinage found in archeological digs, or, much more simply, connection via travel paths (such as the Silk Road). We can use this information to “back out” the network. With this network in hand, we can answer all sorts of questions that we could not answer otherwise. It helps to know whom is connected to whom and what trade cities are connected to others.
Another kind of historical network is personal. These consist of the people that one knows or interacts with. Some of these contacts one knows well (strong ties) and others are casual acquaintances (weak ties). There is a large literature, mainly in sociology and economics, which suggests that the strength of these ties matters for how information (and just about anything else) spreads throughout a network.
Recreating Historical Networks
Personal networks can have a huge influence on historical outcomes. But they can also be really hard to recreate. To recreate personal networks, we tend to need a lot of information about the people in question. Who did they know? How well did they know them? Where were their contacts located? Who did their contacts know? This is hard enough information to get for people in the contemporary world (unless you work for Facebook). It is next to impossible to get for most historical figures.
But it is not impossible. As you go back in history, reconstructing personal networks generally requires focusing on “famous” people: kings, queens, religious figures, or other elites. One needs a lot of information about someone to recreate their network. Famous people tend to leave more historical traces behind, and historians have tended to dig up more information about them. For instance, a fascinating paper by religion scholar Dennis C. Duling reconstructed the network of the early Jesus Movement. This is only possible because there has long been interest in Jesus—who he talked to, where he visited, whom he might have known.
This type of network reconstruction would be impossible for most historical figures. But this exercise can provide fundamentally new insights for those figures for whom we do have enough information to reconstruct their network. This is especially true in situations in which we think one’s network may have been crucial to some social, political, or economic outcome. Given my own interest in religion and historical political economy, one such figure has recently jumped out to me as possibly having an important network: Martin Luther.
Recreating Martin Luther’s Network
The Protestant Reformation was a classic situation in which networks might really matter. Initially, adopting the Reformation was costly. Protestants were burned alive, and religious warfare was endemic. This is where networks may matter. When adoption is costly, knowing that your neighbors adopted is useful—at least you will have allies. Networks also help facilitate the spread of information, which is incredibly important for a movement steeped in ideology.
Fortunately, Luther left enough traces where it is possible to recreate his network. In a recently-published paper with Sascha Becker, Yuan Hsiao, and Steven Pfaff, we attempt to understand the role that Martin Luther’s network played in the spread of the early Reformation. In one sense, we were lucky we were able to do this. Luther was an important person who has fascinated historians for centuries. As such, there has been much work done by a panoply of historians documenting numerous aspects of Luther’s life.
What type of data would one need to reconstruct the network of a man who lived five centuries ago? We do not have information on his day-to-day activities, nor do we have his rolodex. Fortunately, however, many of the letters he wrote survived. Thanks to the good people working on the Luthers Werke project, these letters have been digitized. For the sake of reconstructing Luther’s spatial network, we coded every city in which Luther sent a letter (see below)
Fortunately, we have even more information on Luther than where he sent letters. Due to the meticulous work of Georg Buchwald, we know each city that Luther visited and when he visited it. From the work of Hyojoung Kim and Steven Pfaff, we know the location of each of Luther’s students at the University of Wittenberg. While these data of course do not tell us every person Luther ever met, it does give us a pretty good indication of whom he had some influence with.
Luther’s Network and the Spread of the Reformation
What do we make of Luther’s network? Why do we care? The question we are interested in is the extent to which Luther’s network contributed to the spread of the Reformation. Luther was influential. Whom he was connected to may have therefore mattered. We can conceive of the process as leader-to-follower, originating with Luther and flowing to local elites through personal ties. Luther played the role of a global opinion leader based in Wittenberg. He had ties with local elites in towns across Central Europe, who, in turn, exerted influence in their towns.
But the Reformation may have also spread independently of Luther. Because it was costly to adopt, towns were only likely to adopt if they were connected to another town, via a network, that also adopted. We could therefore envision the Reformation as a “virus” that spread out of Wittenberg. It is certainly a possibility we cannot discount without evidence.
So which was it? Was Luther completely unimportant to the spread of the early Reformation? Would any “heretical” movement coming out of Wittenberg have lit the anti-papal fuse, even in the absence of Luther?
This is unlikely. As we show below, Wittenberg was not very well connected within the Holy Roman Empire (via trade routes). It was, in Luther’s words, “on the edge of civilization.” So maybe the trade network was not enough to spread the Reformation.
But was Luther’s network enough, on its own, to account for the spread of the Reformation? Here, our analysis also finds little evidence in favor. We conduct a simulation analysis and show that Luther would have had to have been improbably “infectious” for his network to fully explain the spread of the Reformation. That is, way too many nodes in Luther’s network would have had to adopt the Reformation because of Luther (and not a myriad of other causes contributing to the success of the Reformation) for this to be the dominant explanation.
So, did Luther’s network matter at all? In short, yes. We argue—and our simulations and regression analyses support—that personal/relational diffusion via Luther’s network combined with spatial/structural diffusion via trade routes. It was the combination of the two diffusion processes that helped Protestantism’s early breakthrough from a regional reform movement to a general rebellion against the Roman Catholic Church. We call this concept “multiplex network diffusion,” because what matters is networks interacting with each other.
The figure below illustrates this idea. It depicts a diffusion story of multiplex networks with multiple diffusion processes. Multiplex ties point to how Luther as an opinion leader mobilized his personal network through an ensemble of letters, visits, and student relationships. Is also shows how Luther’s network blends with the spatial (trade) network to create complex contagion processes operating at the intersection of information flow and social influence.
The Value of Interdisciplinary Work
I’d like to end this post on a note about the research process that went into this paper and what it says about the benefits of interdisciplinary work. Sascha Becker (a fellow economist) and I conceived of something along the lines of this paper a number of years ago over lunch. We both have studied the Reformation in depth from a social science perspective. We agreed that insights on Luther’s role in its spread were sorely lacking. We decided to write our friend, Steve Pfaff (a sociologist), to see if he would have interest in pursuing a project like this. Steve is also an expert on the Reformation and has worked on similar topics in the past. He wrote us back immediately, saying he had already started collecting data for a similar project!
As the three of us started exploring the data on Luther, we realized we needed someone who was an expert on both networks and simulations. Steve told us about one of his students, Yuan Hsiao, who was excellent at both, so we brought him on board (p.s. Yuan is on the market this year and has absolutely blown me away with his skills and insights!). As we proceeded with the project, we soon realized that we were not only making a contribution to the literature on the Reformation, but also to the much larger literature on networks and diffusion. We were able to show using a real life network that multiple diffusion mechanisms can reinforce each other to facilitate spread within a network, even if each mechanism by itself is not sufficient.
This is not an insight we expected to find when starting this project. It was the fruit of an interdisciplinary effort that leaned heavily on sociology, economics, and network theory. I doubt any one or two of us would have been able to write this paper or convincingly test its insights without the help of all of the other co-authors. I also doubt that Sascha and I would have had these insights had we only brought other economists on board.
The research process for this paper was one of the most enjoyable I have been a part of. Of course, the fact that I genuinely like my co-authors and enjoy talking to them helps. But I also think the interdisciplinary nature of our work really made things possible that would not have been possible had we remained in our economics or sociology silos.