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Guía práctica para el análisis y visualización de redes con Visone - Prof. Acosta, Apuntes de Antropología

En este documento, el profesor jürgen lerner presenta una guía práctica para el uso del software visone para la creación, transformación, exploración, análisis y representación de datos de redes. El documento abarca temas como la creación de redes manualmente, la modificación de la apariencia de nodos y bordes, la adición de atributos a actores y vínculos, el uso de plantillas y la creación de legendas, entre otros. Además, se ofrece información sobre el formato de archivo adecuado para guardar la red y sus atributos, así como un ejercicio para dibujar la red social de algunos participantes de este curso.

Tipo: Apuntes

2012/2013

Subido el 30/05/2013

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Analysis and visualization with visone
Jürgen Lerner
University of Konstanz
Egoredes Summerschool Barcelona, 21.–25. June, 2010
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Analysis and visualization with visone

Jürgen Lerner

University of Konstanz

Egoredes Summerschool Barcelona, 21.–25. June, 2010

About visone.

Visone is the Italian word for mink. In Spanish visón.

visone is a software for the visual creation, transformation exploration, analysis, and representation of network data.

Outline.

Introducing the visual graph editor.

Analysis and visualization of networks in visone.

Advanced attribute management.

task assignment

Dynamic networks.

visone’s visual graph editor.

In this trail you’ll learn to use the graphical interface of visone I (^) how networks can be manually created in visone; I (^) changing the graphical appearance of nodes and edges; I (^) how attributes (e. g., age, gender, type of relationship) can be added to actors and ties; I (^) using templates and creating a legend; I (^) selecting actors and ties with certain characteristics; I (^) exporting image files suitable for publication.

Cheat sheet: which file format should I choose?

You have to distinguish between (I) saving/exporting the whole network I (^) Whenever possible, use GraphML. That’s the only format which saves everything (structure, attributes, and graphics). I (^) Export in Ucinet or Pajek format (dl or net) is supported. I (^) For many other software, including Excel, SPSS, STATA, R, S-Plus,... ⇒ adjacency matrices in csv. Note: doesn’t save graphics nor attributes. (II) saving/exporting an image of the network I (^) If possible use vector-graphics: pdf, eps, svg. They give better quality and need smaller file size. I (^) Otherwise use pixel-based graphics: png, jpg,...

Cheat sheet: which file format should I choose?

You have to distinguish between (I) saving/exporting the whole network I (^) Whenever possible, use GraphML. That’s the only format which saves everything (structure, attributes, and graphics). I (^) Export in Ucinet or Pajek format (dl or net) is supported. I (^) For many other software, including Excel, SPSS, STATA, R, S-Plus,... ⇒ adjacency matrices in csv. Note: doesn’t save graphics nor attributes. (II) saving/exporting an image of the network I (^) If possible use vector-graphics: pdf, eps, svg. They give better quality and need smaller file size. I (^) Otherwise use pixel-based graphics: png, jpg,...

Cheat sheet: which file format should I choose?

You have to distinguish between (I) saving/exporting the whole network I (^) Whenever possible, use GraphML. That’s the only format which saves everything (structure, attributes, and graphics). I (^) Export in Ucinet or Pajek format (dl or net) is supported. I (^) For many other software, including Excel, SPSS, STATA, R, S-Plus,... ⇒ adjacency matrices in csv. Note: doesn’t save graphics nor attributes. (II) saving/exporting an image of the network I (^) If possible use vector-graphics: pdf, eps, svg. They give better quality and need smaller file size. I (^) Otherwise use pixel-based graphics: png, jpg,...

Cheat sheet: which file format should I choose?

You have to distinguish between (I) saving/exporting the whole network I (^) Whenever possible, use GraphML. That’s the only format which saves everything (structure, attributes, and graphics). I (^) Export in Ucinet or Pajek format (dl or net) is supported. I (^) For many other software, including Excel, SPSS, STATA, R, S-Plus,... ⇒ adjacency matrices in csv. Note: doesn’t save graphics nor attributes. (II) saving/exporting an image of the network I (^) If possible use vector-graphics: pdf, eps, svg. They give better quality and need smaller file size. I (^) Otherwise use pixel-based graphics: png, jpg,...

Exercise: visone’s visual graph editor.

Draw the social network of (some of) the participants of this course , as far as you are aware of it. I (^) Include characteristics of the actors. I (^) Include different types of relationships. I (^) Encode the actors’ characteristics in graphical variables. I (^) Don’t forget yourself. I (^) Don’t take this too seriously;-) Export an image of your network.

You might do this in groups of two or three to foster discussion.

Outline.

Introducing the visual graph editor.

Analysis and visualization of networks in visone.

Advanced attribute management.

task assignment

Dynamic networks.

Introduction to the dataset.

Personal networks collected by interviewing ≈ 500 migrants in Catalonia and Florida. (http://www.egoredes.net/)

From each respondent ( ego )

  1. (questions about ego) country of origin, years of residence, skin-color, health, language skills,...
  2. (alters) 45 people known to the respondent
  3. (questions about alters) origin, country of residence,...
  4. (ties) which alters know each other

Here, analyze one personal network of a migrant from the Dominican Republic to the USA.

Overview: analysis of networks in visone.

visone distinguishes between three different levels of analysis.

  1. (indexing) computation of node-level / edge-level properties. I (^) centrality (importance) of nodes and edges; I (^) clustering coefficient; I (^) distance to selected nodes;
  2. (grouping) computation of dense subgroups or partitioning the network into groups.
  3. (siena) interface to the RSiena software. I (^) data preparation and model specification in visone; I (^) visualization of the estimated model and its fit to the observed network;

Cheat sheet: which visualization should I take?

What for? Layout the network to give a clear picture of its structure. I (^) Usually: use the quick layout button. I (^) For comparison with other software, visone offers other algorithms (MDS, spring embedder, spectral, circular,... ). I (^) Link routing bends edges to reduce crossings. I (^) Label placement reduces overlap.

Highlight node and edge properties. I (^) Attributes (external or network analytic) can be mapped to graphical variables (size, color, label, coordinates,... ). I (^) For displaying importance: centrality and status layout.

Geometric transformation. Rotate, reflect, translate, scale, Procrustes analysis.

Cheat sheet: which visualization should I take?

What for? Layout the network to give a clear picture of its structure. I (^) Usually: use the quick layout button. I (^) For comparison with other software, visone offers other algorithms (MDS, spring embedder, spectral, circular,... ). I (^) Link routing bends edges to reduce crossings. I (^) Label placement reduces overlap.

Highlight node and edge properties. I (^) Attributes (external or network analytic) can be mapped to graphical variables (size, color, label, coordinates,... ). I (^) For displaying importance: centrality and status layout.

Geometric transformation. Rotate, reflect, translate, scale, Procrustes analysis.