Who We Are

• NUG (Nauchno-Uchebnaya Gruppa) on Digital Literary Studies at the Centre for Digital Humanities at HSE, Moscow

Objective

• create and maintain a corpus of Russian-language drama from the middle of the 18th to the first third of the 20th century
• XML-based markup standard TEI (Text Encoding Initiative)
• main goal: a large-scale social network analysis of dramatic texts ("distant reading")

Distant-Reading Showcase (2016)

Poster with network graphs of 465 German-language dramas (1730–1930).
Released at DHd2016, Leipzig. – DOI: 10.6084/m9.figshare.3101203.v1.

But Today …

… we focus on didactics:

How do we extract or create social
network data from literary texts?

Network Theory …

"… is the study of graphs as a representation of (…) relations between discrete objects." (Wikipedia)

Small example network graph with
8 vertices (nodes) and 10 edges:

Source: Wikimedia Commons

Network Graph for Ostrovsky’s "Groza"

Based on interactions.

What Is an Interaction?

• our approach (inspired by Solomon Marcus, 1973): two characters are linked to each other if both are performing a speech act in a given segment (scene) of a play
• this is our operationalisation, but there are other approaches for the extraction of a social network from a literary text, it really depends on your research question

Formalisation of Interactions

Source,Target,Weight
Барыня,Варвара,2
Барыня,Кабанов,1
Барыня,Кабанова,1
Барыня,Катерина,2
Борис,Варвара,4
Борис,Глаша,1
Борис,Дикой,1
Борис,Женщина,1
Борис,Кабанов,1
Борис,Кабанова,1
Борис,Катерина,3
Борис,Кудряш,4
Борис,Кулигин,3
Борис,Первый,1
Борис,Феклуша,1
...

Ostrovsky’s "Groza", interactions encoded in a CSV list (comma-separated values).

RusDraCor Showcase

https://rusdracor.shinyapps.io/showcase/ (by Ivan Pozdniakov)

Automatisation? (1/2)

• our project is based on the automatic extraction of social networks from larger TEI corpora
• but operationalising this kind of extraction is a non-trivial, sometimes ambiguous act, even if we talk about highly structured texts like dramas

Automatisation? (2/2)

• as an introduction to the difficulties of an automatisation we developed our tool ezlinavis
• purpose is not to compete with more sophisticated methods of extracting networks from literary texts
• intended for didactic use in teaching, to take first steps from theory to practice

Screenshot

ezlinavis in action.

A Much More Versatile Kind of Formalisation

# ДЕЙСТВИЕ ПЕРВОЕ
## ЯВЛЕНИЕ ПЕРВОЕ
Петр
Анисья
Акулина
Никита
## ЯВЛЕНИЕ ВТОРОЕ
Петр
Анисья
## ЯВЛЕНИЕ ТРЕТЬЕ
Петр
Анисья
Акулина
## ЯВЛЕНИЕ ЧЕТВЕРТОЕ
Петр
Анисья
Акулина
Анютка
## ЯВЛЕНИЕ ПЯТОЕ
Анисья
Петр
Акулина
...

Tolstoy’s "Vlast’ t’my", a line-by-line listing of characters per scene.

Live Demo

https://dlina.github.io/ezlinavis/

Production Notes

• open source program, can be installed on your own server/localhost
• React.js for building the interface
• preview graph in the right column is generated live, we used Sigma.js for this
• CSV format is created live, based on the content entered (or copied-and-pasted) by the user in the left row
• this 4-column CSV can be saved and imported directly into Gephi or other network visualisation software

Postprocessing in Gephi (Example)

Puschkin’s "Boris Godunov" after postprocessing a CSV file in Gephi (done by German Palchikov).

Bibliography

• Bode, K.: The Equivalence of 'Close' and 'Distant' Reading; Or, Toward a New Object for Data-Rich Literary History. MLQ 78.1 (2017). (Preprint here.)
• Fischer, F.; Göbel, M.; Kampkaspar, D.; Trilcke, P. (2015). Digital Network Analysis of Dramatic Texts. DH2015.
• Jannidis, F. (2017): Netzwerke. In: Jannidis F.; Kohle, H.; Rehbein, M. (eds.): Digital Humanities. Eine Einführung, 147–161.
• Moretti, F. (2011): Network Theory, Plot Analysis. New Left Review 68, 80–102.
• Tolstoy, L. (1887): Vlast’ t’my. (Digital copy via rvb.ru.)

Acknowledgements

This talk was prepared within the framework of the Academic Fund Program at the National Research University Higher School of Economics (HSE) in 2017–2018 (grant No 17-05-0054) and by the Russian Academic Excellence Project "5-100".