The new version of the build-in layout ForceAtlas is now released. It is scaled for small to medium-size graphs, and is adapted to qualitative interpretation of graphs. The equations are the same as ForceAtlas 1, but there are more options and innovative optimizations that make it a very fast layout algorithm.
It is good enough to deal with very small graphs (10 nodes) and fast enough to spatialize 10,000 nodes graphs in few minutes, with the same quality. If you have time, it can deal with even bigger graphs.
Update Gephi (Help > Check for Updates) to get this new layout.
Force Atlas 2:
- Is a continuous algorithm, that allows you to manipulate the graph while it is rendering (a classic force-vector, like Fruchterman Rheingold, and unlike OpenOrd)
- Has a linear-linear model (attraction and repulsion proportional to distance between nodes). The shape of the graph is between Früchterman & Rheingold’s layout and Noack’s LinLog.
- Features a unique adaptive convergence speed that allows most graphs to converge more efficiently
- Proposes summarized settings, focused on what impact the shape of the graph (scaling, gravity…). Default speed should be the good one.
- Now features a Barnes Hut optimization (performance drops less with big graphs)
Force Atlas 2 features these settings:
- Scaling: How much repulsion you want. More makes a more sparse graph.
- Gravity: Attracts nodes to the center. Prevents islands from drifting away.
- Dissuade Hubs: Distributes attraction along outbound edges. Hubs attract less and thus are pushed to the borders.
- LinLog mode: Switch ForceAtlas’ model from lin-lin to lin-log (tribute to Andreas Noack). Makes clusters more tight.
- Prevent Overlap: Use only when spatialized. Should not be used with “Approximate Repulsion”
- Tolerance (speed): How much swinging you allow. Above 1 discouraged. Lower gives less speed and more precision.
- Approximate Repulsion: Barnes Hut optimization: n² complexity to n.ln(n) ; allows larger graphs.
- Approximation: Theta of the Barnes Hut optimization.
- Edge Weight Influence: How much influence you give to the edges weight. 0 is “no influence” and 1 is “normal”.
Force Atlas 2 was created by Mathieu Jacomy at the Sciences Po Médialab (Paris), founding member of the Gephi Consortium.
Gephi blog 
[…] still looks compressed as hell. That’s what we have got the layout algorithms for. Append the Force Atlas 2 algorithm for instance . This will enable you to make out some very clear clusters if there are […]
[…] and importing the data, it is important to generate an initial structural view of the entities. Force Atlas 2 is an effective algorithms since studies have identify that organizational structure can be […]
[…] vamos a centrar en el método de “Force Atlas 2“ (En siguientes artículos hablaremos de los diferentes métodos y configuraciones). Quedando algo […]
[…] networks are always a blob after import. The ForceAtlas2 layout algorithm is good for up to 10,000 nodes, but it really makes my CPU fan spin when I give it […]
Nice Tuto! Thanks a lot – I’m currently running ForceAtlas2 on 1K nodes but its seems to take ages to run….