Networks gephi and a little bit of palladio
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Networks: Gephi (and a little bit of Palladio). @ DJWrisley #RRSI2014, UTSC, May 2014. networkstheory, analysis, visualization. Network analysis – a term encompassing a wide variety of practices with applications throughout (social) scientific and digital humanistic domains

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Networks: Gephi (and a little bit of Palladio)

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Networks gephi and a little bit of palladio

Networks: Gephi (and a little bit of Palladio)


#RRSI2014, UTSC, May 2014

Networks theory analysis visualization

networkstheory, analysis, visualization

  • Network analysis – a term encompassing a wide variety of practices with applications throughout (social) scientific and digital humanistic domains

  • “Network theory concerns itself with the study of graphs as a representation of either symmetric relations or, more generally, of asymmetric relations between discreteobjects.” (Wikipedia, 6 italicized words are mine—all debatable in humanist circles)

  • Network theory has its own conceptual vocabulary to express relationships between objects (e.g. betweenness, centrality, density, path length, modularity) – how can we interpret these analytical terms for humanities data?

Network theory analysis visualization 2

networktheory, analysis, visualization (2)

  • Social network analysis SNA looks at relationships between actors – what is the nature of interaction?

  • Latour adds objects in actor-network theory ANT – what could the relation of an actor and an object be?

  • Networks once drawn (drawn by Moretti- Network Theory, Plot Analysis), are now digitally created and manipulated

  • Powerful way of exploring multidimensional multi-scalar data (Brughmans)

Some beginning remarks

Some beginning remarks

@ elijahmeeks on the network

@ElijahMeeks on the network

  • "The network is not a social network or geographic network or logical network but rather a primitive object capable of and useful for the modeling and analysis of relationships between a wide variety of objects."


Basic principles 1

Basic principles (1)

  • Not all study of networks is quantitative (Brughmans on Malkin, 2011), just as every mapping is not made of spatial data onto a map interface

  • Digital tools for network visualization and analysis use tabular data (quantification can be a challenge, metadata adds qualitative contours)

  • Digital tools like Gephi allow both for networks to be explored visually, and for static visuals of them to be exported. It does not allow for sharing.

  • Data visualization is a kind of “problem-posing”; we should avoid fetishizing the final visual. (McCosker/Wilke) – “diagrammatic” thinking

Basic principles 2

Basic Principles (2)

  • Tabular data used by network viz platforms are of two basic sorts

    • Nodes (discrete entities in a network, and any fixed metadata about them – gender, geospatial data)

    • Edges (specific instances of relations between nodes)

      NB: Gephi does generate a nodes table if it is missing (option: create missing nodes)

Different tools

Different tools

Network visualization tools

Network visualization tools

  • Gephi (standalone)

    • Elijah Meeks



    • Non proprietary code – plug ins

  • Palladio (web-based)

  • NetXL

  • Sci²

    • Scott Weingart

    • Indiana MOOC on visualization

  • Points of comparison: performance, usability, filter, formats of data ownership, data portability, cost

  • Example 1

    Example 1

    NB: Examples Increase in Scale

    Networks gephi and a little bit of palladio

    One textRamon Llull, Book of the Lover and the Beloved (late 13th)

    Llull data snapshot @ djwrisley @ tracey dh nodes left edges right

    Llull Data Snapshot (@djwrisley @tracey_dh) nodes (left) edges (right)

    Llull s social networks @ djwrisley @ tracey dh

    Llull’s “social” networks(@djwrisley @tracey_dh)

    Llull social networks minus the narrator @ djwrisley @ tracey dh

    Llull “social” networks, minus the narrator (@djwrisley @tracey_dh)

    Algorithmic llull

    Algorithmic llull


    Force Atlas

    Tinker tailor soldier spy @hayay44

    Tinker tailor soldier spy(@hayay44)

    Tinker tailor the karla collection @hayay44

    Tinker tailor, “the karla collection” (@hayay44)

    Networks gephi and a little bit of palladio

    14th c medieval french (around jean de meun) – stylometric analysis of 70+ textsJ Richards (Wuppertal – Germany)

    Stylometric data sample

    Stylometric data sample

    • Open file RRSI stylo experiment

    Networks gephi and a little bit of palladio

    250+ Texts of medieval french – test case for power of stylometry given dialectal difference (@DJWrisley and J Richards)

    • Parts of gephi interface

    • Visualizing the network using the same file

    Facebook networks via @ grandjeanmartin

    Facebook networks via @Grandjeanmartin

    Networks of newspapers 19 th c via @ ryancordell

    Networks of Newspapers 19th c via @ryancordell

    Image orbis the stanford geospatial network model of the roman world

    Image: ORBIS: The Stanford Geospatial Network Model of the Roman World

    Spaces and texts a network with gephi @ djwrisley

    Spaces and Texts – a Network with Gephi @djwrisley

    Vie de saint louis text place @ djwrisley

    Vie de Saint Louis TEXT - PLACE @djwrisley

    Jerusalem aspected by form @ djwrisley

    Jerusalem – aspected by form @djwrisley

    Paul s examples

    Paul’s Examples

    A brief comparison

    A Brief Comparison -



    • standalone

    • open source

    • Established large user community = many plug-ins

    • Takes a while to learn

    • Science/humanities use

    • Not easy to share without giving away data

    • Network statistics

    • web-based

    • free

    • Relatively new

    • Learning curve low

    • Specifically for the humanities

    • simple to deal with data multi-dimensionality

    • Data is not kept

    • “without any barriers”

    Palladio example space in literature

    Palladio example – Space in Literature

    • Live Example using file “distorted VMP data”

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