DVI - Data Visualization Interface
asoter_1_hashtagTop_9_cec6fcb9
MUID
Seed Node
Depth
Type
Amount
Created At
Username Bot
Iteration
Status
Finished At
Graphology.js ForceAtlas Layout
ID
Network will include:
Standard
Text_AI_Dict
Text_AI_OOV
Image_AI
Select the data used to feed the graph. Standard [hashtags, posts, users]. Text_AI: Hashtags classificated by [Northamerica city list, Graffiti terms, Railroad terms] Image_AI: Post classificated by graffti types [tag, wildstyle, 3D, monikers, bomba (trowhup])]
Node Minimum Degree
Minimum entrance degree of node, smaller will be deleted form graph. Default will be 0
Should we clean not related
text_ai_entitites
to term
"graffiti"
, numbers only and non latin chars?
true
false
Gravity
Should the node’s sizes be taken into account?
true
false
Use the Barnes-Hut approximation to compute repulsion in O(n*log(n)) rather than default O(n^2), n being the number of nodes.
true
false
Barnes-Hut approximation theta parameter
outboundAttractionDistribution
true
false
Use Noack’s LinLog model?
true
false
scalingRatio
slowDown
strongGravityMode
true
false
nodeFixedSize
true
false
initialLayout
random
circlepack
autoGravityScale
auto
manual
Build graph
Network Graph
Graph Stats
Total nodes:
-
Total edges:
-
Dropped nodes:
-
Nodes after drop:
-
Edges after drop:
-
Density:
-
Simple size:
-
Weighted size:
-
Click History:
Delete
Node Stats
Nodes clicked:
-
Neighbors of node:
-
nodeReducerDepth
*
selectedNeighbors
selectedNeighborsNeighbors
statsVis
graph
node
mediaVis
true
false
Start
Stop
Screenshot
initial size & colors
drop not inferenced
deletePostHashtags
Compute centrality stats
(betweenness, closeness, degree, eigenvector [not working with big networks], pagerank)
betweenness centrality
closeness centrality
degree centrality
pageranksizecentrality
Compute louvain stats
(louvain)
Color louvain stats
(just after computelouvain it's executed)
countnodeType
Response @ console.log
countnodeTypeState
Response @ console.log
contarNodosConUsuariosVinculados
Response @ console.log