Network Profile
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Influence Score
6.31%
of network
Direct Connections
7
Node & Network Strength Details
×
How is this calculated? The math continuously tracks how strongly this post is connected to the rest of the website.
Every tag forms a network link. The pie charts below show each connected post's base strength (PV) and influence (IV) as a share of this post's direct neighbourhood.
Outbound
3
Tags on post
Inbound
4
Posts tagging this
Base Node Strength
12
Base Node Influence
0.75
Connected Nodes
10
Strength Share (vs Direct Neighbours)
This Post (6.12%) Copenhell (8.16%) Dermot O'Reilly (4.59%) Christina Markus Lassen (2.04%) Faculty of Copenhagen Business School (2.04%) Leonard Seabrooke (2.04%) Copenhagen bus line 666 (2.04%) Copenhell 2011 (2.04%) Royal Library Garden, Copenhagen (1.02%)
Dominant nodes (excluded from chart) David Heinemeier Hansson 41.33% Copenhagen Business School 28.57%
Influence Share (vs Direct Neighbours)
This Post (6.31%) Royal Library Garden, Copenhagen (16.82%) Copenhagen Business School (9.61%) Dermot O'Reilly (8.41%) Copenhell (8.41%) Christina Markus Lassen (8.41%) David Heinemeier Hansson (8.41%) Faculty of Copenhagen Business School (8.41%) Leonard Seabrooke (8.41%) Copenhagen bus line 666 (8.41%) Copenhell 2011 (8.41%)
Connected Network (How neighbours affect this node)
Top Network Boosters (Highest Multipliers)
Weakest Connections (Lowest Multipliers)
Connection Health Audit (Red = broken 1-way link)
Last calculated math cycle: May 2, 1:02 AM
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Nearest Locations 📍
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Copenhagen, Capital Region of Denmark, Denmark
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