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Sir William Dunn School of PathologyScience Area, OxfordDepartment of Physics, University of OxfordDepartment of Earth Sciences, University of OxfordDepartment of Computer Science, University of OxfordDepartment of Engineering Science

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Department of Engineering Science, University of Oxford

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Analyzing Network Connections...

Loading Map...

Nearest Locations

  • 📍
    Department of Engineering Science0.0 km away
  • 📍
    Denys Wilkinson Building0.0 km away
  • 📍
    Department of Computer Science, University of Oxford0.1 km away
  • 📍
    Department of Computer Science0.1 km away
  • 📍
    Department of Physics, University of Oxford0.2 km away

Network Profile

Overall Strength
i
2.99% of network
(35.8K)
Strength Breakdown
  • This Post (2.99%)
  • Science Area, Oxford (52.24%)
  • Department of Physics, University of Oxford (23.88%)
  • Department of Computer Science, University of Oxford (11.94%)
  • Department of Earth Sciences, University of Oxford (5.97%)
  • Sir William Dunn School of Pathology (1.49%)
  • Department of Engineering Science (1.49%)
Influence Score
i
21.28% of network
(5.6)
Influence Breakdown
  • This Post (21.28%)
  • Department of Computer Science, University of Oxford (21.28%)
  • Science Area, Oxford (14.89%)
  • Department of Earth Sciences, University of Oxford (10.64%)
  • Department of Physics, University of Oxford (10.64%)
  • Sir William Dunn School of Pathology (10.64%)
  • Department of Engineering Science (10.64%)
Direct Connections 3

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, 1) = 1

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

// 3. Exponential Network Values (accumulating 6 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 2 *
                           ( 8 [Department of Computer Science, University of Oxford] *
                            35 [Science Area, Oxford] *
                            4 [Department of Earth Sciences, University of Oxford] *
                            16 [Department of Physics, University of Oxford] *
                            1 [Sir William Dunn School of Pathology] *
                            1 [Department of Engineering Science]
                           )

                         = 35.8K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 2 *
                           ( 2 [Department of Computer Science, University of Oxford] *
                            1.4 [Science Area, Oxford] *
                            1 [Department of Earth Sciences, University of Oxford] *
                            1 [Department of Physics, University of Oxford] *
                            1 [Sir William Dunn School of Pathology] *
                            1 [Department of Engineering Science]
                           )

                         = 5.6
Outbound 2 Tags on post
Inbound 1 Posts tagging this
Connections 6 Total nodes
Base Node Strength 2
Base Node Influence 2
Strength Share (vs Direct Neighbours)
2.99% (35.8K overall)
  • This Post (2.99%)
  • Science Area, Oxford (52.24%)
  • Department of Physics, University of Oxford (23.88%)
  • Department of Computer Science, University of Oxford (11.94%)
  • Department of Earth Sciences, University of Oxford (5.97%)
  • Sir William Dunn School of Pathology (1.49%)
  • Department of Engineering Science (1.49%)
Influence Share (vs Direct Neighbours)
21.28% (5.6 overall)
  • This Post (21.28%)
  • Department of Computer Science, University of Oxford (21.28%)
  • Science Area, Oxford (14.89%)
  • Department of Earth Sciences, University of Oxford (10.64%)
  • Department of Physics, University of Oxford (10.64%)
  • Sir William Dunn School of Pathology (10.64%)
  • Department of Engineering Science (10.64%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Department of Computer Science, University of Oxford ↗
Str: 8Inf: 2
Science Area, Oxford ↗
Str: 35Inf: 1.4
Department of Earth Sciences, University of Oxford ↗
Str: 4Inf: 1
Department of Physics, University of Oxford ↗
Str: 16Inf: 1
Sir William Dunn School of Pathology ↗
Str: 1Inf: 1
Department of Engineering Science ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Department of Engineering Science ↗
Str: 1Inf: 1
Sir William Dunn School of Pathology ↗
Str: 1Inf: 1
Department of Physics, University of Oxford ↗
Str: 16Inf: 1
Department of Earth Sciences, University of Oxford ↗
Str: 4Inf: 1
Science Area, Oxford ↗
Str: 35Inf: 1.4
Department of Computer Science, University of Oxford ↗
Str: 8Inf: 2

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

Outbound Tags (2)
Department of Engineering Science
BROKEN LINK
Science Area, Oxford
Inbound Posts (1)
Science Area, Oxford
Last calculated: Jul 30, 5:43 PM
Oxford, Oxfordshire, United Kingdom32

Related Content

Locations

  • Science Area, Oxford
  • Department of Computer Science, University of Oxford
  • Department of Earth Sciences, University of Oxford
  • Department of Physics, University of Oxford

Topics

  • Sir William Dunn School of Pathology
  • Department of Engineering Science