In the Western Church, Augustine’s dictum “The Word comes to the element; and so there is a sacrament, that is, a sort of visible word” could be the bumper sticker for sacramental understanding. Don’t mind that every tradition comes to its own interpretation of what that means. Robert Jenson, however, summarizes the foundation of that phrase as, “when the Bible’s God speaks to us… it comes to and then with some ‘element,’ some piece of the external word.”[i] For my tradition this visibility allows us to grasp, sometimes literally, grace as when bread is placed in our hands in the Eucharist.
How do we grasp other intangibles though? God makes grace tangible in sacraments, but how are we able to grasp the many ways we exist in relationship with others? Are there ways for us to understand the ecosystem of relationships that we inhabit? Let’s my personal network to think about visualizing personal networks.
Thankfully the answer is yes. While it does not involve good bread or tasty wine, the best way to visualize relationships, perhaps surprisingly, is math. Graphical techniques can help us create maps of our relationships with others, and the web those relationships weave. A very good introduction to understanding network science can be found on the website for the UC Davis Data Lab.
In thinking about my network, I am going to limit my network, because mapping my entire personal network would be a grueling, nigh-impossible task. I decided to think about the people I have interacted with through my previous podcast, that is, people whom I had brought on as guests. I also included people who had talked with me about publicly presenting a topic or leading a discussion.
 |
| The visual representation of my personal network |
I also need to define what kind of network model I am looking at. In the introduction site I linked above, there are two kinds of networks. I decided to use a two-node network to see where the people I have interacted with have mostly been connected to me. I chose four areas of life that have been important to me. First, I looked to see who was connected to the Evangelical Lutheran Church in America. Second, I looked to people who are active in academia. Third, I included people who have some public connection to discussing popular culture beyond mere fandom. Finally, I looked at people who have some connection to Campus Ministry. A sample of my data matrix is shown. If someone has a connection to an area, the corresponding box gets a value of one, otherwise the value is zero.
Choosing a two-node network seemed most appropriate in this case because it shows the arenas I inhabit, as a pastor and as a public theologian. This analysis felt more helpful than the way my network are connected to each other. Not surprisingly, because I looked at the guests on my podcast, almost everyone listed has some connection to popular culture. That makes sense given my podcast looked at the intersection of popular culture and theology and faith. However, because I have been asked or I have asked others to speak on topics outside of popular culture (e.g. White Christian Nationalism, Artificial Intelligence), I have a limited number of folks who have no connection to popular culture.
Likewise I have a great number of connections to the Evangelical Lutheran Church in America (ELCA). As a pastor in that denomination, this element makes sense. Additionally, it serves as a possible warning. I do not give any data in this visualization about member node demographics. This image does not show if my connections are men or women, white or people of color. It does not give up any other religious affiliation. I could have included a node of ecumenical partners with the ELCA, but I did not. The ELCA however is in some reckoning the whitest denomination in the United States. If my network leaned as heavily toward the ELCA as it did toward popular culture, I could easily have shared only white voices. Refining this visualization in the future, I believe I would separate the people’s nodes into different sectors like “White women,” “White men,” Women of color,” “Men of Color.” This delineation could help me suss out those distinctions further.
Even rudimentary analyses like this one give us some ability to understand what values shape our networks beyond our own internal voice saying, “of course, I have a diverse network.” I could easily have deluded myself, knowing that one of my guiding principles with the podcast was including the voices of women and people of color, voices often kept out of conversations of theology or popular culture, or even the intersection. This visualization becomes a visible word of that principle.
