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Caffeine dependence

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Recreational drug use

Analyzing Network Connections...

Network Profile

Overall Strength
i
5.13% of network
(3.1K)
Strength Breakdown
  • This Post (5.13%)
  • Animations of caffeine (1.28%)
  • Caffeine biosynthesis (1.28%)
  • Caffeine dehydrogenase (1.28%)
  • Caffeine-Free Coca-Cola (1.28%)
  • Chemical structures of caffeine (1.28%)
  • Health effects of caffeine (1.28%)
  • Amphetamine dependence (1.28%)
  • Bob Beckel (1.28%)
  • Khat trade and consumption (1.28%)
Dominant nodes (excluded from chart)
Caffeine 62.82%Drug addiction 20.51%
Influence Score
i
8.33% of network
(1)
Influence Breakdown
  • This Post (8.33%)
  • Caffeine (8.33%)
  • Animations of caffeine (8.33%)
  • Caffeine biosynthesis (8.33%)
  • Caffeine dehydrogenase (8.33%)
  • Caffeine-Free Coca-Cola (8.33%)
  • Chemical structures of caffeine (8.33%)
  • Health effects of caffeine (8.33%)
  • Drug addiction (8.33%)
  • Amphetamine dependence (8.33%)
  • Bob Beckel (8.33%)
  • Khat trade and consumption (8.33%)
Direct Connections 4

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, 2) = 2
$outbound = max(1, 2) = 2

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 2 * 2 = 4
Base_Influence (IV) = $inbound / $outbound = 2 / 2 = 1

// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 4 *
                           ( 49 [Caffeine] *
                            1 [Animations of caffeine] *
                            1 [Caffeine biosynthesis] *
                            1 [Caffeine dehydrogenase] *
                            1 [Caffeine-Free Coca-Cola] *
                            1 [Chemical structures of caffeine] *
                            1 [Health effects of caffeine] *
                            16 [Drug addiction] *
                            1 [Amphetamine dependence] *
                            1 [Bob Beckel] *
                            1 [Khat trade and consumption]
                           )

                         = 3.1K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Caffeine] *
                            1 [Animations of caffeine] *
                            1 [Caffeine biosynthesis] *
                            1 [Caffeine dehydrogenase] *
                            1 [Caffeine-Free Coca-Cola] *
                            1 [Chemical structures of caffeine] *
                            1 [Health effects of caffeine] *
                            1 [Drug addiction] *
                            1 [Amphetamine dependence] *
                            1 [Bob Beckel] *
                            1 [Khat trade and consumption]
                           )

                         = 1
Outbound 2 Tags on post
Inbound 2 Posts tagging this
Connections 11 Total nodes
Base Node Strength 4
Base Node Influence 1
Strength Share (vs Direct Neighbours)
5.13% (3.1K overall)
  • This Post (5.13%)
  • Animations of caffeine (1.28%)
  • Caffeine biosynthesis (1.28%)
  • Caffeine dehydrogenase (1.28%)
  • Caffeine-Free Coca-Cola (1.28%)
  • Chemical structures of caffeine (1.28%)
  • Health effects of caffeine (1.28%)
  • Amphetamine dependence (1.28%)
  • Bob Beckel (1.28%)
  • Khat trade and consumption (1.28%)
Dominant nodes (excluded from chart)
Caffeine 62.82%Drug addiction 20.51%
Influence Share (vs Direct Neighbours)
8.33% (1 overall)
  • This Post (8.33%)
  • Caffeine (8.33%)
  • Animations of caffeine (8.33%)
  • Caffeine biosynthesis (8.33%)
  • Caffeine dehydrogenase (8.33%)
  • Caffeine-Free Coca-Cola (8.33%)
  • Chemical structures of caffeine (8.33%)
  • Health effects of caffeine (8.33%)
  • Drug addiction (8.33%)
  • Amphetamine dependence (8.33%)
  • Bob Beckel (8.33%)
  • Khat trade and consumption (8.33%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Caffeine ↗
Str: 49Inf: 1
Animations of caffeine ↗
Str: 1Inf: 1
Caffeine biosynthesis ↗
Str: 1Inf: 1
Caffeine dehydrogenase ↗
Str: 1Inf: 1
Caffeine-Free Coca-Cola ↗
Str: 1Inf: 1
Chemical structures of caffeine ↗
Str: 1Inf: 1
Health effects of caffeine ↗
Str: 1Inf: 1
Drug addiction ↗
Str: 16Inf: 1
Amphetamine dependence ↗
Str: 1Inf: 1
Bob Beckel ↗
Str: 1Inf: 1
Khat trade and consumption ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Khat trade and consumption ↗
Str: 1Inf: 1
Bob Beckel ↗
Str: 1Inf: 1
Amphetamine dependence ↗
Str: 1Inf: 1
Drug addiction ↗
Str: 16Inf: 1
Health effects of caffeine ↗
Str: 1Inf: 1
Chemical structures of caffeine ↗
Str: 1Inf: 1
Caffeine-Free Coca-Cola ↗
Str: 1Inf: 1
Caffeine dehydrogenase ↗
Str: 1Inf: 1
Caffeine biosynthesis ↗
Str: 1Inf: 1
Animations of caffeine ↗
Str: 1Inf: 1
Caffeine ↗
Str: 49Inf: 1

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

Outbound Tags (2)
Caffeine
Drug addiction
Inbound Posts (2)
Caffeine
Drug addiction
Last calculated: Jun 23, 8:31 PM
20

Related Content

Topics

  • Health effects of caffeine
  • Drug addiction
  • Caffeine
  • Amphetamine dependence
  • Animations of caffeine
  • Bob Beckel
  • Caffeine biosynthesis
  • Khat trade and consumption
  • Caffeine dehydrogenase
  • Caffeine-Free Coca-Cola
  • Chemical structures of caffeine