Application of social network analysis methods to the study of the Old Norse sagas, with a primary emphasis on Icelandic family sagas. Reading and discussion in English. No prior knowledge of computing required.

The Icelandic Family Sagas are an intriguing window onto the social world of 10th and 11th century Iceland, seen through the authorial lens of late medieval writers. A striking characteristic of the sagas is the abundance of characters that interact on and across complex social networks as they first initiate and then try to resolve conflicts. Indeed, an enduring question in saga studies is how enmity arises between groups and how that enmity is eventually resolved. Since the main conflict resolution mechanism in early Icelandic society was the blood feud, the sagas can be quite violent at times. Yet nearly all sagas end with some form of a peaceful resolution and a return to social balance. Just as important as enmity is the concept of friendship. How is friendship perceived, how is friendship nurtured, and how is friendship violated in the saga? Another important consideration is that of status. How is status conceptualized, and to what extend does status influence aspects of community formation, conflict, and peace making? While the majority of saga scholarship has focused on a few main characters (the hero, the villain), or classes of characters (strong women), in developing analyses of these social conflicts, an approach that considers all of the characters in a saga (and possibly across multiple sagas), may help us develop a better understanding of the dynamic complexity of these well-known works of late medieval fiction. With the rise of social media, such as Facebook, Twitter, Instagram, SnapChat, WhatsApp, TikTok and even Tinder, there has been a concomitant increase in attention on the analysis of social networks. While Social Network Analysis (SNA) has long been a staple of sociology departments (cf. the excellent classes on Social Network Analysis here at Berkeley), certain literary traditions, such as the Icelandic Family Saga, are prime candidates for this type of analysis in the context of literary studies. Consequently, the question we ask in this class is what type of analytic information gain do we get by applying approaches from SNA to the study of the Icelandic family sagas? In the course of our investigations, we will explore how character interactions can be used as the basis of developing a social network view of the “stage” on which the saga action plays out. We will examine how best to model the saga as a dynamic social network, and learn about metrics and analytical approaches from SNA that deepen our understanding of saga actions. SNA provides us with an additional opportunity to explore hypothetical situations (what would have happened to the network had Skarpheðinn not insulted his interlocutors?), and recognize alternative social pathways that may have led to other types of community formations. Over the course of the semester, students will learn about sagas and saga scholarship, as well as spend time working closely with several family saga texts. Similarly, students will learn important aspects of network analysis, including types of networks (directed, undirected, n-partite), general network metrics (size, diameter, clustering coefficient, density), as well as various topological features (centrality measures, paths, community detection, motifs) and decompositions on the network (k-core, k-peel, fixed points). We will also learn about dynamic processes such as preferential attachment. Students will also learn about network graph visualization. Books Kellogg, Robert, ed. 2001. The Sagas of Icelanders. Penguin Classics. Harmondsworth: Penguin. Required. Fortunato, Santo, et al. 2019. A First Course in Network Science. Cambridge: Cambridge UP. Required. Watts, Duncan. Six Degrees: The Science of a Connected Age. New York: W.W. Norton. Optional. Kadushin, Charles. 2011. Understanding Social Networks: Theories, Concepts and Findings. Oxford: Oxford UP. Optional. Easley, David and Jon Kleinberg. 2010. Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge: Cambridge UP. Recommended. Additional required readings can be found on the course website. Software (all required) • Gephi • Casos-ORA (this is optimized for PC—if you are on Mac or Linux, you will need to build a virtual machine to run this software—see course website for details on creating a virtual windows machine) • Cytoscape • Microsoft Excel with PowerQuery OR OpenRefine • Optional: Google Colab or Jupyter Notebooks (follow along in Fortunato et al for the various imports of NetworkX and bringing a csv file in through Pandas as a data frame) • Optional: A text editor such as BBEdit or Sublime Datasets (downloadable from course website)—these are generally csv files or graphml files.

Repeat Rules

Course is not repeatable for credit.