Citation Analysis in Research Evaluation (Information Science & Knowledge Management)
Citation Analysis in Research Evaluation (Information Science & Knowledge Management)
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Analysing social networks within bibliographical data
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
Studying the source code of scientific research
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Scientific literature has itself been the subject of much scientific study, for a variety of reasons: understanding how results are communicated, how ideas spread, and assessing the influence of areas or individuals. However, most prior work has focused on extracting and analyzing citation and stylistic patterns. In this work, we introduce the notion of ‘scienceography', which focuses on the writing of science. We provide a first large scale study using data derived from the arXiv e-print repository. Crucially, our data includes the "source code" of scientific papers--the $\hbox{\LaTeX }$ source--which enables us to study features not present in the "final product", such as the tools used and private comments between authors. Our study identifies broad patterns and trends in two example areas--computer science and mathematics--as well as highlighting key differences in the way that science is written in these fields. Finally, we outline future directions to extend the new topic of scienceography.