bipartite drawing

We need your help (user study in graph drawing)

We are currently conducting an online user study. It would be a great help if you could support us by participating in this study. I can’t say too much about the study here without influencing the results, but I promise I will write about the outcome and the design of our experiments when we are finished.

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swatwads teaser

Dynamic Citation Graph

Almost a year ago I had a post about citation networks of interconnected communities. Simply speaking, I displayed a citation network (which paper cites which) of two related conferences. As conferences pairs I picked GD/WG, ICALP/ESA, and SWAT/WADS. All these conferences had their proceedings published by Springer, which made it easier to get the data via crawling through the springerlink portal.

Although the pictures were really nice (rendered in gephi) I wanted to have a more dynamic visualization. This weekend I finally found the time to prepare something. I picked the biggest component (82 nodes) in the SWAT/WADS network, since it was the smallest interesting (sub)graph I found. My goal was to let the user filter the data by year and get a dynamically increasing citation graph over time.

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MiniMetro Subway Layout Game

Today I stumbled upon a puzzle game where the goal is to layout a metro map. The game is called MiniMetro see here for the official webpage. It is currently under development in some sort of beta version – but it can already purchased. It runs on Windows, Mac, Ubuntu and Steam. Hey, a metro network drawing game, how cool is that. Of course, I had to give it a try (bought via the Humble Store).

Early stage in designing a subway in St. Petersburg.

Early stage in designing a subway in St. Petersburg.

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Citation graphs of interconnected communities

As a follow-up to my previous post about the citation graph of the Graph Drawing conference I computed a few more drawings with gephi. This time I have concentrated on visualizing connections between conferences with a similar scope. I improved my “springerlink-crawler”. In the current version I first scan all the titles and then I scan for references where the matching is done by title. By this I will also detect references to journal versions if they have the same title. Again the citation graphs are very sparse, since they only reflect citations within the conferences. The data set is very likely not 100% accurate, but my impression is that it is good enough to illustrate a few interesting things.

GD and WG

Graph drawing is a smaller part of the Workshop on Graph-Theoretic Concepts in Computer Science (WG). The graph drawing conference (GD) also targets geometric graph theory. As a big difference, GD is more self-referential, whereas there are considerably less links within the WG citation network. The picture shows the combined citation network of both conferences. Papers appeared in WG are colored yellow, GD papers are drawn red. Many of the WG papers are isolated nodes or show up in very small components. There exists one big component. As one can see, there is a big part of the network that belongs to WG. It contains more classical graph theory papers. The GD dominated part is densely connected. In this part one can find a smaller fraction of WG papers.

GD WG citation networg

GD WG citation network.

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Paper citation graph for GD

Here are a few pictures from the citation network of the Graph Drawing conference (GD). The nodes represent the papers that were published in GD. There are 821 papers in the data set. A edge is pointing from node a to node b, if the paper associated to node a cites the paper associated to node b. Of course this only encodes the citations within the GD conference. In particular, it ignores the fact that many papers were published subsequently as journal versions. However it is nice to expore this data. There are about 40% isolated nodes, and 20% of the nodes have only degree 1. The network has one big connected component and several very small components. I have generated a few pictures of the big component, listing only papers that have at least one GD citation. The size of the nodes reflect the in-degree (citations) of a paper.

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