Citation network centrality: a scientific awards predictor?
Abstract: The $K$-index is an easily computable centrality index in complex networks, such as a scientific citations network. A researcher has a $K$-index equal to $K$ if he or she is cited by $K$ articles that have at least $K$ citations. The $K$-index has several advantages over Hirsh's $h$-index and, in previous studies, has shown better correlation with Nobel prizes than any other index given by the {\em Web of Science}, including the $h$-index. It is plausible that researchers who are the most connected to other scientifically well-connected researchers are the most likely to be doing important work and more likely to be awarded major prizes in a given area. However, the correlation found does not imply causation. Here we perform an experiment using the $K$-index, producing a shortlist of twelve candidates for major scientific prizes, including the Physics Nobel award, in the near future. For example, our top-12 $K$-index list naturally selects the 2019 Nobel laureate, James Peebles. The list can be updated annually and should be compared to laureates of the following years
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.