Network Profile
Influence Score
7.49%
of network
(1.37148)
Direct Connections
8
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
4
Tags on post
Inbound
4
Posts tagging this
Base Node Strength
16
Base Node Influence
1
Connected Nodes
12
Strength Share (vs Direct Neighbours)
- This Post (7.55%)
- Einherjer (14.15%)
- Ragnar Vikse (4.25%)
- Rune Bjelland (4.25%)
- Thundra (1.89%)
- Arne Marton Tangjerd (1.89%)
- Harald Helgeson (1.89%)
- Ruben Osnes (1.89%)
- Thor Erik Helgesen (1.89%)
- Erik Elden (1.89%)
- Kirsten JÃ ̧rgensen (1.89%)
Dominant nodes (excluded from chart)Evig Natt 30.19%Ole Kristian Løvberg 26.42%
Influence Share (vs Direct Neighbours)
- This Post (7.49%)
- Einherjer (8.99%)
- Ole Kristian Løvberg (8.57%)
- Evig Natt (7.49%)
- Thundra (7.49%)
- Ragnar Vikse (7.49%)
- Rune Bjelland (7.49%)
- Arne Marton Tangjerd (7.49%)
- Harald Helgeson (7.49%)
- Ruben Osnes (7.49%)
- Thor Erik Helgesen (7.49%)
- Erik Elden (7.49%)
- Kirsten JÃ ̧rgensen (7.49%)
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, 1:42 PM
Analyzing Network Connections...
👁️ 26 Views
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