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Abstract:
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We have collected and cleaned two network data sets: Coauthorship and Citation networks for statisticians. The data sets are based on all research papers published in four of the top journals in statistics from 2003 to the first half of 2012. We analyze the data sets from many different perspectives. For example, we have identified the most prolific/collaborative/highly cited authors. We have also identified a handful of ``hot" papers, suggesting ``Variable Selection" as one of the ``hot" areas. Also, we have also identified about 15 meaningful communities or research groups, including large-size ones such as ``Spatial Statistics", ``Large-Scale Multiple Testing", ``Variable Selection" as well as small-size ones such as ``Dimensional Reduction", ``Bayes", ``Quantile Regression", and ``Theoretical Machine Learning". Our findings shed light on research habits, trends, and topological patterns of statisticians. The data sets provide a fertile ground for future research on social networks. The research is continued in an ongoing project, where the data set is about $20$ times larger, covering papers published in about 20 statistical journals spanning 30-40 years.
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