What is the organizing principle for large topics?

Abstract

We know a great deal about how to identify the topics that researchers are working on. One can use citations and/or text to identify about one hundred thousand document clusters from either the Scopus database or the WoS database. For purposes of discussion, we refer to these document clusters as topics. In our models there are about a thousand very large topics and tens of thousands of small topics. But why doesn’t topic size follow an expected linear Zipfian distribution? Is it possible that there is a different organizing principle for large vs. small topics? In this study, we explore the possibility that the organizing principle for large topics is the continued use of very expensive tools (such as specialized equipment, specialized databases and specialized software). For our initial exploration, we use grant size (NSF or NIH grants in excess of $5 million annually) as proxy for preferential investment in specialized tools. By using links between 52,097 grants and tens of thousands of topics, we will test whether large topics get more (than expected) funding from large grants and, by inference, expensive tools are an organizing principle for large topics.