Digital Humanities Crash-Course

April 19 — 26

Course slides & materials

danilsko.github.io/DHelsinki

Warning

This presentation is Non-Linear

Use SPACE to go forward, SHIFT+SPACE to go back

Plan for today

  1. Networks Intro
  2. What can we formalise (and study) as a network/graph
  3. Human Networks
  4. Humanities Networks
  5. Practice with Gephi & Ezlinavis: HOWTO
    • import and work with existing network datasets
    • build your own networks

Same plan in informal Russian :)

  • Что за сети? Что за анализ?
  • сети (графы) в реальном мире
  • Те самые «шесть рукопожатий»: сети из людей
  • С кем дружил Фрэнсис Бэкон и кому платили короли: сети в гуманитарных науках
  • Пушкин на посылках и «коммунистическая» пьеса: что можно увидеть в вымышленных сетях?
  • Практика в Gephi и Ezlinavis

networks 101

A network (a graph)

What can be represented as a network?

Practically anything

Bridges

Seven Bridges of Königsberg by Euler

This is how network theory came about

Transportation networks

Directed graph

Another transportation network

Weighted graph

INTERNET

Wikipedia

And by the way

data like this is easily extractible from Wiki using DBpedia or Wikidata (+SPARQL)

...and of course, social networks!

Lut's try live

Lut's try live

But actually, this is real rocket social science!

Social Network Analysis

Origins in 1930-es: Kurt Levin, Jacob Moreno

check it out at Martin Grandjean's website!

Social Network Analysis

Manchester Anthropology School (Max Gluckman and followers) in the 50-es

Social Network Analysis

'Harvard Breakthrough' in the 60-es (Harrison White and followers)

The (Infamous) Six Degrees of Separation

(Теория шести рукопожатий)

Small World Experiment

Small World Experiment

Social Network Analysis

New Wave with new data

Networks: now in the humanities!

Who knew whom in Britain 500 years from now

  • Проект Six Degrees of Francis Bacon (шесть рукопожатий Фрэнсиса Бэкона)
  • Более 13.000 человек, более 200.000 связей
  • Извлечено из Oxford Dictionary of National Biography
  • sixdegreesoffrancisbacon.com

People of Medieval Scotland

poms.ac.uk

RusDraCor

rus.dracor.org

(Shiny RusDraCor)

shiny.dracor.org

It’s pretty (and fashionable)

Ondrej Tichy, Charles University

But actually, networks give you a combination of visual and formal (mathematical) analysis

Centrality

Centrality of A = 5

What about this one

This is called betweenness centrality

So, networks help us

  • Measure the 'importance' of a separate node (based on centrality measures)
  • Analyse paths in a networks (e.g. information flow)
  • also, communities extraction!

Commmunity detection: Karate Club

Commmunity detection: Karate Club

  • A social network of a karate club studied by Wayne W. Zachary from 1970 to 1972
  • Links capture interactions between the club members outside the club
  • During the study a conflict arose between the administrator "John A" and instructor "Mr. Hi" (pseudonyms), which led to the split of the club into two.

    • Commmunity detection: Karate Club

  • Half of the members formed a new club around Mr. Hi
  • members from the other part found a new instructor or gave up karate.
  • Basing on collected data Zachary assigned correctly all but one member of the club to the groups they actually joined after the split
  • Link to the paper (1977)

    • Commmunity detection: Karate Club

    The process leading to fission is viewed as an unequal flow of sentiments and information across the ties in a social network. This flow is unequal because it is uniquely constrained by the contextual range and sensitivity of each relationship in the network. The subsequent differential sharing of sentiments leads to the formation of subgroups with more internal stability than the group as a whole, and results in fission

    Zachary's matrix

    Zachary's network visualization

    Karate Club: my try in Gephi

    Karate Club Club

    Networks in Fiction

    ...not limited to literature

    One of the first computable literary networks

    Donald Knuth. Stanford GraphBase (1994)

    Simple Stories

    Schweizer T., Schnegg M. Die soziale Struktur der. „Simple Storys“: Eine Netzwerkanalyse. (1998)

    The Marvel Universe

    Rotates Around Captain America!

    The Marvel Universe

  • Alberich, R., Miro-Julia, J., Rossello, F. (2002), Marvel universe looks almost like a real social network.
  • P. M. Gleiser. How to become a superhero. Journal of Statistical Mechanics: Theory and Experiment, (09):P09020, 2007.

    • The Marvel Universe

    Alice in Wonderland

    ..and many others followed

    • James Stiller, Daniel Nettle, and Robin I. M. Dunbar (2003) The Small World of Shakespeare’s Plays.Human Nature 14(4):397---408.
    • “Weak Links and Scene Cliques Within the Small World of Shakespeare,” Journal of Cultural and Evolutionary Psychology 3, no. 1 (2005)
    • Elson, D. K., Dames, N. and McKeown, K. (2010), Extracting Social Networks from Literary Fiction, Proceedings of ACL 2010, Uppsala, Sweden.
    • J. Rydberg-Cox. Social Networks and the Language of Greek Tragedy. Journal of the Chicago Colloquium on Digital Humanities and Computer Science, 1(3):11, 2011.
    • Agarwal A., Corvalan A., Jensen J., Rambow O. (2012), Social network analysis of Alice in Wonderland. Proceedings of the NAACL HLT 2012 Workshop on Computational Linguistics for Literature, pages 88–96, Montreal, Canada.

    Reinvention of Literary Networks by Moretti

    Scaling Up

    And now on Russian data

    Classicism vs Romanticism in Russian Corpus

    (rus.dracor.org)

    Gavrila Pushkin — is he important?

    Gavrila the messenger

    Bityagovsky (double agent)

    Bitkov (spy on Pushkin)

    Now — hands on with Gephi!

    slides.com/danilsko/gephi