Ranked influence typology

Description

Detect the type of influence that each node holds within a network.

The algorithm detects not only the influence played by every node inside a network, but also how it contributes to the overall network (for example the word-of-mouth, content creation, and diffusion of information).

Given a large dataset of connections as input, it provides a ranking of all nodes by influence score, reporting their typology of influence. Every node plays a certain role in the network and affects the other nodes in its own different way.

Typologies of influence

Ranked influence typology algorithm is capable to detect 19 categories of influencers.

Role	Description	Graph view
Amplifier	A node that talks more than listens. It increases the flow of information.
Blackhole	When the node absorbs only a huge amount of information and does not emit anything. This node is totally inactive in producing information.
Bridge	It is a node that ties together two hubs allowing a direct passage of information.
Chain	It is a link in a directed word-of-mouth chain. What it receives will be passed to the next unique connected node.
Channeler	When a node directs the information channeled by a reducer or by a dam into a chain.
Connector	A node that only connects together two common nodes.
Dam	It listens too much but talks very little. It may also act as an information selector, collecting a lot of information to share what is the most relevant. It could be a big barrier to the spread of news too.
Emitter	It does not listen, it is only a source of information.

How to use it

watchcomplexity.influence.typology(edges=Array[Object])

Field	Type	Required	Description
edges	[object]	yes	An array of all the connections between nodes.
edges.from	string	yes	The node's name or id where the edge start: the source node of the link.
edges.to	string	yes	The node's name or id where the edge end: the target node of the link.
edges.weight	number	yes	The weight of the connection: how strong is the bond among the linked nodes.

Example

// The list of edges
const edges = [
  {from: "Napoleon", to: "Myriel", weight: 1},
  {from: "Mme.Magloire", to: "Myriel", weight: 10},
  {...}
];
// Measure the influence score and detect the influence roles
const nodes = watchcomplexity.influence.typology(edges);

That will return:

{
 ranking: 
   [
      {node: "Marius", role: "Hub", score: 100},
      {node: "Courfeyrac", role: "Amplifier", score: 93.68029739776952},
      {node: "Enjolras", role: "Reducer", score: 92.93680297397769},
      {node: "Fantine", role: "Amplifier", score: 89.96282527881041},
      ...,
      {node: "Mme.Hucheloup", role: "Emitter", score: 39.405204460966544},
      {node: "Anzelma", role: "Low emitter", score: 34.94423791821562},
      {node: "Pontmercy", role: "Reducer", score: 33.08550185873605},
      ...
      {node: "OldMan", role: "Emitter branch", score: 1.4869888475836461},
      {node: "Napoleon", role: "Emitter branch", score: 0}
   ],
  nodes: 77,
  edges: 254,
  distribution:  {
    Blackhole: 0,
    Vulcano: 0,
    Channeler: 0,
    Chain: 0,
    Bridge: 1,
    Connector: 3,
    'Emitter branch': 15,
    'Receiver branch': 2,
    Receiver: 2,
    Emitter: 4,
    'Low emitter': 9,
    Idle: 0,
    Transceiver: 5,
    Tophub: 0,
    Hub: 1,
    Dam: 6,
    Reducer: 12,
    Megamplifier: 7,
    Amplifier: 10
  }
}