WikiLeaks Cablegate Reference Network Visualization

cable2graph is a collection of tools to create interactive HTML5/CSS3/SVG visualizations from graph data.

It is primarily written for the cables.csv file that contains the raw WikiLeaks cablegate data.

Three types of graphs are currently supported:

undirected graph based on the manual references between cables
weighted directed graph based on the sender and receiver of cables
bipartite graph based on the TAGS value of each cable

INSTALL

install igraph 0.6 C library and Python extension module
install jinja2

$ pip install jinja2
Download and unpack the zip archive of the github repository

https://github.com/wlwardiary/cable2graph/archive/master.zip

USAGE

The typical workflow is divided in four steps:

extract features from the cables.csv (optional)
build the full graph
split the graph
create the visualization

SHORT VERSION

$ ./c2g full.graphml
$ ./splitgraph --source full.graphml -d /tmp --multilevel --clusters
$ ls /tmp/*graphml > /tmp/list-of-graphs
$ ./g2svg -t graph-timeline.tmpl -i /tmp/list-of-graphs
$ ./g2idx -i /tmp/list-of-graphs -d /tmp
$ open /tmp/index.html

EXTRACT

Extract features from the cables.csv into smaller plain text files stored in the data directory.

This step is optional. All files created by extract are included in the repository. A full run can take around 2-4 minutes.

$ ./extract cables.csv

See below at the DATA section for more details.

GRAPH

Create the large graph full.graphml with a file size of ~170MB.

$ ./c2g full.graphml

The graph contains the following node and edge values:

message reference number (MRN) as label
the place part of the MRN
missing with a value of 0 or 1 if the cable is referenced but not included in the cables.csv
unix timestamp for the time the cable was send
the classification of the cable
cable caption (currently only partial data)
node degree
pagerank
authority
constraint
node betweenness

Node betweenness is based on the giant component of the full graph. Pre-calculated values are loaded from data/betweenness. Calculation of the Brandes betweenness takes around nine hours for the ~100,000 nodes and ~143,000 edges of the giant component.

SPLIT

Split the large graph into smaller clusters and communities.

$ ./splitgraph --source full.graphml --multilevel --clusters

The --cluster option will export connected components but not the giant.

The giant component can be split using four different community detections.

multilevel (Blondel, Guillaume, Lambiotte, Lefebvre, 2008)
leading eigenvector (Newman)
fastgreedy (Clauset, Newman, Moore, 2004)
walktrap (Pons, Latapy)

Use the --giant option to save the giant component into a file.

The full graph or the giant component can be visualized with Gephi using the OpenOrd layout. The browser can display a SVG with around 800-1000 nodes without performance issues.

NEIGHBORHOOD

The nbh tool creates the neighborhood graph for a given node. For multiple labels the directly related nodes are grouped together.

$ echo "10EXAMPLE1" > list
$ echo "09EXAMPLE2" >> list
$ ./nbh full.graphml list

Not all cables have a neighborhood and nbh will never create the same graph twice.

VISUALIZATION

create HTML file with inline SVG from any .graphml:

$ ./g2svg -g example.graphml

or use a list of graph files as source:

$ ls cluster*graphml > list-of-clusters
$ ./g2svg -i list-of-clusters

Two templates are currently included:

svg.tmpl: graph with sidebar
graph-timeline.tmpl: graph with timeline

$ ./g2svg -t graph-timeline.tmpl -g example.graphml

The default layout algorithm is the force directed Kamada-Kawai (1989). The --layout option can be used to specify any layout algorithm supported by igraph v0.6.

Useful are:

fruchterman_reingold or fr
grid_fruchterman_reingold or gfr
tree
kamada_kawai or kk

For a full list run:

$ pydoc igraph.Graph.layout

USAGE WITH GEPHI

For the integration with gephi existing layouts stored as x,y node attributes are supported by g2svg. Use the gephi File -> Export function.

Step by step how-to: https://github.com/wlwardiary/cable2graph/wiki/gephi

GRAPH INDEX

The g2idx tool creates a index.html file for a list of given graphs showing classification, TAGS and graph properties.

$ ls *graphml > index-list
$ ./g2idx -i index-list

MAIN TOOLS

extract: feature extraction from cables.csv
c2g: create a graph from the reference data
splitgraph: split a graph into clusters and communities
nbh: create a neighborhood graph for a list of MRN's
g2svg: render graph layout and create svg

MISC TOOLS

t2g: create a graph from the TAGS data
r2g: create a graph with the "from -> to" routing data
c2txt: extract body and header from cables.csv
calcdates: estimate date for missing MRN's
gen_colors: create a random color for every place (see svg.css)

DATA

data/wikileaks.org.map: MRN to url mapping
data/all_ids.list: all known MRN's
data/betweenness: pre-calculated betweenness values form the giant
data/cable_ids.list: all MRN's that exist in the cables.csv
data/captions.list: cable captions mentioned in the REF: field
data/classifications.list: MRN to classifications mapping
data/clique-big.list: list of all clusters
data/clique.list: list of all bigger cluster
data/dates.list: all known dates for each MRN
data/dates_missing.list: estimated dates for missing MRN's
data/diff_cnt.list: how often is a missing MRN referenced
data/edges.list: reference network
data/embassy.list: embassy names from the MRN
data/from_to.list: sender and receiver network
data/locations.list: Locations name from the cvs header
data/missing_mrn.list: referenced but missing MRN's
data/ref_ids.list: referenced MRN's from cvs header
data/ref_regex_ids.list: referenced MRN's from cable body
data/routing.codes: telegram routing codes
data/subjects.list: full extracted subject for each MRN
data/tags.program: all program TAGS
data/tags.subject: all subject TAGS
data/tags_edges.list: TAGS network

COPYLEFT

GPLv3

CONTACT

https://twitter.com/datapornstar

Cable2graph

Install / Use

README