Here’s how we’ve applied this question so far on the Digital Mitford Project.
#Cytoscape tutorial series#
Consider networks based on who is being talked about (or "name-dropped") in a given context: Which people (or organizations, or other named entities) are mentioned together in the same blog posts, tweets, YouTube comment feeds, or chapters in an autobiography? For example, say you've been coding the people who are mentioned in a series of letters: Which people are most often mentioned together in the same letter across the body of letters? You might filter that to study which people turn up in the same letters together during an interesting span of the letter-writer's life.Here is a co-citation network analysis that is actually about the scholarly topic of social network analysis, based on bibliographies of 133 papers. Co-citation networks essentially plot such relationships when they map which authors are cited together most frequently in a scholarly journal's bibliographies.This graph uses color and texture to differentiate among time-periods and cultural origin. Which people show up together in the same contexts? Who shows up in the same place at the same time-say in the context of a club, or a chat room? Or where are the musicians performing: which venues host which musicians over a period of time? Here is Helena Bermúdez Sabel's social network graph of troubadours, showing which noble and royal courts hosted them over five periods in medieval Spain.Here are some examples of research topics that explore co-occurrence networks: This tutorial is designed especially for people working on humanities-based XML projects, and my examples will focus on humanities applications for network analysis with an emphasis on networks of co-occurence (networks of things that appear together in the same shared contexts), but those working on different kinds of research questions or not working with XML at all may find portions of this tutorial useful. Plotting a network model might help to predict the spread of a virus, or a breakdown in overloaded circuitry, or it might help to identify the most influential individuals in a royal court over two generations. If we can plot a readable model of a network, we can make it possible to locate individual points that are highly important and isolate areas that are vulnerable to influence. Networks are structures of linkages and interactions, and in studying them we attempt to organize relationships, considering how close or how distant particular points are from each other, or how centrally important something or someone is to a collective. What We Can Learn from Network Analysis and Networks of Co-Occurrence.
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