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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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.

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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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