Network Profile
Influence Score
9.66%
of network
(1.28565)
Direct Connections
4
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.
// 1. Base variables (minimum value of 1 to prevent zero-multiplication issues)
Outbound ($in) = max(1, 2) =
2
Inbound ($out) = max(1, 2) =
2
// 2. Node Base Values
Base Strength (PV) = $in × $out = 2 × 2 =
4
Base Influence (IV) = $in ÷ $out = 2 ÷ 2 =
1
// 3. Network Exponential Values (accumulating 9 direct neighbours)
Network Strength (CV) = Node PV × (Π Neighbour PVs) =
243.8B
Network Influence (TV) = Node IV × (Π Neighbour IVs) =
1.28565
Outbound
2
Tags on post
Inbound
2
Posts tagging this
Base Node Strength
4
Base Node Influence
1
Connected Nodes
9
Strength Share (vs Direct Neighbours)
- This Post (0.94%)
- Alphastates (19.10%)
- mike o'dowd (9.91%)
- Catherine Dowling (2.12%)
- Graham Gilligan (2.12%)
- stevie kavanagh (2.12%)
- Markéta Irglová (1.42%)
- Gerry Horan (0.94%)
- CAT DOWLING (0.94%)
Dominant nodes (excluded from chart)Graham Hopkins 60.38%
Influence Share (vs Direct Neighbours)
- This Post (9.66%)
- Markéta Irglová (14.48%)
- Catherine Dowling (9.66%)
- Gerry Horan (9.66%)
- Graham Gilligan (9.66%)
- Alphastates (9.66%)
- CAT DOWLING (9.66%)
- stevie kavanagh (9.66%)
- Graham Hopkins (9.66%)
- mike o'dowd (8.28%)
Connected Network (How neighbours affect this node)
Top Network Boosters (Highest Multipliers)
Weakest Connections (Lowest Multipliers)
Connection Health Audit (Red = broken 1-way link)
Inbound Posts (2)
No other posts link to this one yet.
Last calculated math cycle: May 5, 4:55 AM
Analyzing Network Connections...
👁️ 24 Views
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