Part of working with textual data is the classification of the text in question in some way or another. Now, there are many different ways of classifying a text: epoch, school of thought or authorship are only a few examples. This article will deal with genres or rather with the questions and problems concerning them. Every day we let our reading be guided by genre classifications: We open up a book with a cover saying “Thriller” and automatically expect a more or less suspense-packed plot. Or if it says “Novel”, we hope to read a rather sweet and romantic story. But can these classifications really be trusted? (For example: An English speaking reader would expect a “novel” to be rather long. A German speaking reader on the other hand might expect a “novel” to be rather short, because the term resembles the German term “Novelle”, even though “Roman” would be the actual translation.) And what do they help us regarding ancient Egyptian texts?
“To mine and to tie – Text mining and network analysis for historians”
This was the title of the 9th Historical Network Research Workshop, which took place at Ruhr-University Bochum, organized by the SeNeReKo team. More than 40 participants to the Ruhr Area to take part in programming introductions and other workshops, to listen to speeches by their colleagues from different research fields, having a network speed dating, and discussing lively, but in relaxed atmosphere the past, present and future of network research and Digital Humanities.
This post is part of a series of posts about text network analysis. Each post will discuss one approach to algorithmically creating networks from texts. See the primer for an introduction and the list of posts.
Recalling the networks 101, a network in its formal representation consists of nodes, i.e. the basic elements of my data, and edges, i.e. relations between the nodes. When creating a network from a text, one has to answer two basic questions:
- What are my nodes?
- What constitutes a relation between two nodes?
This post is part of a series of posts about text network analysis. Each post will discuss one approach to algorithmically creating networks from texts.
Historical network analysis—or, more generally, network analysis in the digital humanities—is in most cases an application of Social Network Analysis in the fields of history or literary studies. It shares with sociological approaches its focus on social actors, or: people. In contrast to sociology, DH applications mostly focus on dead (history) or fictional (literary studies) people.