Explorative Visualization of Citation Patterns in Social Network Research*

We propose a visual representation of bibliographic data based on shared references. Our method employs a distance metric that is derived from bibliographic coupling and then subjected to fast approximate multidimensional scaling. Its utility is demon­ strated by an explorative analysis of social network publications that, most notably, depicts the genesis of an area now commonly referred to as network science. However, the example also illustrates some common pitfalls in bibliometric analysis.

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