Known data-sets

SocNetV can recreate easily one of the following known data-sets:

From File menu select "Create known data set" or press F7. A dialog will appear where you select one of the data-sets above. Press OK and the network will be displayed in the canvas.

Random network creation

SocNetV can create a random network for you. At the moment, it can create the following types of random networks:

Scale-free

SocNetV generates random scale-free networks of n nodes according to the Barabási–Albert (BA) model which uses a preferential attachment mechanism.

The algorithm starts with the given \( m_0 \) connected nodes. In each step a single new node is added, along with \( m \) edges to existing nodes.

The probability that the new node will connect to an existing node \( i \) is: \( p_i = \frac { (α + d_i ^ p) } { \sum_j {d_j} } \) where:
\( α \) the initial 'attractiveness' of each node,
\( d_i \) the degree of node \( i \)
\( \sum_j {d_j} \) the sum of degrees of all pre-existing nodes \( j \)

if \( α = 0 \) and \( p = 1 \) then the preferential attachment is linear (BA model).

Small Worlds

SocNetV creates small worlds using the Watts and Strogatz model. According to that model, a 'small world' is a random network with short average path lengths and high clustering.
Given the desired number of nodes N, the mean degree K (assumed to be an even integer), and a special parameter \( \beta \), satisfying \( 0 \le \beta \le 1 \) and \( N\gg K \gg \ln(N)\gg 1 \), the model constructs an undirected graph with N nodes and \( \frac{NK}{2} \) edges in the following way:

From the menu Network select Create Random Network > Small World (or press Shift+W).
You will be asked for the number of nodes N, their mean degree K and a rewiring probability \( \beta \).

Erdos-Renyi networks

According to G(n, p) model (Erdos-Renyi), a random network is created by connecting nodes randomly.

Each edge is included in the graph with equal probability P, independently of the other edges.

From the menu Network select Create Random Network > Erdos-Renyi (or press Shift+R).

You will be asked for the number of nodes and an edge probability.

Ring lattices

Ring lattices (or physicist's lattices) are 'random' networks where all nodes are positioned in a ring.

Each one has the same even degree (number of edges) d with her "neighbourhood", namely she is linked with the d/2 nodes before and d/2 nodes after her.

For instance in a 4-lattice of 10 nodes, node 6 will be linked with 4, 5, 7 and 8.

To create a ring lattice network click Network > Create Random Network > Ring Lattice (or press Shift+L).

You will be asked for the number of nodes and the degree of each node.

d-regular networks

These are random network where each node have the same number of "neighbours", aka the same degree d.

Nodes are arbitrarily linked with each other other.

Web Crawler

SocNetV includes a simple web crawler, which consists of two parts: a spider and a parser.

The spider visits a given initial URL (i.e. a website or a webpage) and downloads its HTML code.
The parser scans the code for 'href' links to other pages (internal or external) and adds them to a queue of URLs (called frontier).
As URLs are added in the queue, the spider visits them and downloads their HTML which is scanned for more links by the parser, and so on...
The end result is the 'network' of all visited webpages as nodes and their real links as edges.

Please note that the parser searches for 'href' links only in the body section of the HTML code.

To start the web crawler, go to menu Network > Web Crawler or press Shift+C. A dialog will appear, where you must enter the initial web page (seed).

You can also set the maximum nodes/pages (default 600) and what kind of links to crawl: internal, external or both.
By default the spider will crawl both internal and external links.