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Rohit BhattacharyaAkshat TanejaGuillotine KyodaiGuillotineKabir MahajanTakar Nabam

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Connected Musicians

  • Guillotine Kyodai
  • Takar Nabam

Analyzing Network Connections...

Network Profile

Overall Strength
i
2.70% of network
(60)
Strength Breakdown
  • This Post (2.70%)
  • Guillotine Kyodai (5.41%)
  • Akshat Taneja (2.70%)
  • Kabir Mahajan (2.70%)
  • Rohit Bhattacharya (2.70%)
  • Takar Nabam (2.70%)
Dominant nodes (excluded from chart)
Guillotine 81.08%
Influence Score
i
12.77% of network
(1.67)
Influence Breakdown
  • This Post (12.77%)
  • Guillotine Kyodai (25.53%)
  • Akshat Taneja (12.77%)
  • Kabir Mahajan (12.77%)
  • Rohit Bhattacharya (12.77%)
  • Takar Nabam (12.77%)
  • Guillotine (10.64%)
Direct Connections 2

Node & Network Details

How is this calculated?

The math continuously tracks how strongly this post is connected to the rest of the network. Every tag forms a 2-way link. The base stats determine personal node strength, and the pie charts below show this node's share against its direct neighbours.

// 1. Base variables (floored at 1 to prevent zero-multiplication math errors)
$inbound = max(1, 1) = 1
$outbound = max(1, 1) = 1

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 1 * 1 = 1
Base_Influence (IV) = $inbound / $outbound = 1 / 1 = 1

// 3. Exponential Network Values (accumulating 6 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 2 [Guillotine Kyodai] *
                            1 [Akshat Taneja] *
                            1 [Kabir Mahajan] *
                            1 [Rohit Bhattacharya] *
                            1 [Takar Nabam] *
                            30 [Guillotine]
                           )

                         = 60

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 2 [Guillotine Kyodai] *
                            1 [Akshat Taneja] *
                            1 [Kabir Mahajan] *
                            1 [Rohit Bhattacharya] *
                            1 [Takar Nabam] *
                            0.8333 [Guillotine]
                           )

                         = 1.67
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 6 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
2.70% (60 overall)
  • This Post (2.70%)
  • Guillotine Kyodai (5.41%)
  • Akshat Taneja (2.70%)
  • Kabir Mahajan (2.70%)
  • Rohit Bhattacharya (2.70%)
  • Takar Nabam (2.70%)
Dominant nodes (excluded from chart)
Guillotine 81.08%
Influence Share (vs Direct Neighbours)
12.77% (1.67 overall)
  • This Post (12.77%)
  • Guillotine Kyodai (25.53%)
  • Akshat Taneja (12.77%)
  • Kabir Mahajan (12.77%)
  • Rohit Bhattacharya (12.77%)
  • Takar Nabam (12.77%)
  • Guillotine (10.64%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Guillotine Kyodai ↗
Str: 2Inf: 2
Akshat Taneja ↗
Str: 1Inf: 1
Kabir Mahajan ↗
Str: 1Inf: 1
Rohit Bhattacharya ↗
Str: 1Inf: 1
Takar Nabam ↗
Str: 1Inf: 1
Guillotine ↗
Str: 30Inf: 0.8333
Weakest Connections (Lowest Multipliers)
Guillotine ↗
Str: 30Inf: 0.8333
Takar Nabam ↗
Str: 1Inf: 1
Rohit Bhattacharya ↗
Str: 1Inf: 1
Kabir Mahajan ↗
Str: 1Inf: 1
Akshat Taneja ↗
Str: 1Inf: 1
Guillotine Kyodai ↗
Str: 2Inf: 2

Connection Health Audit (Red = broken 1-way link)

Outbound Tags (1)
Guillotine
Inbound Posts (1)
Guillotine
Last calculated: Jun 14, 9:13 AM
13

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Topics

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  • Kabir Mahajan