Statistics in everyone's backyard: an impact study via citation network analysis

TL;DR

This study analyzes citation networks to assess how statistical research influences other scientific fields, revealing increasing interdisciplinary impact through bibliometric data and advanced clustering techniques.

Contribution

It introduces a novel approach using personalized PageRank with conductance for identifying relevant statistical research areas related to external topics, with theoretical guarantees.

Findings

Diversity of citing fields has increased over time.

Statistical research increasingly impacts other scientific disciplines.

Citation patterns align with expert knowledge and intuition.

Abstract

The increasing availability of curated citation data provides a wealth of resources for analyzing and understanding the intellectual influence of scientific publications. In the field of statistics, current studies of citation data have mostly focused on the interactions between statistical journals and papers, limiting the measure of influence to mainly within statistics itself. In this paper, we take the first step towards understanding the impact statistics has made on other scientific fields in the era of Big Data. By collecting comprehensive bibliometric data from the Web of Science database for selected statistical journals, we investigate the citation trends and compositions of citing fields over time to show that their diversity has been increasing. Furthermore, we use the local clustering technique involving personalized PageRank with conductance for size selection to find the most relevant statistical research area for a given external topic of interest. We provide theoretical guarantees for the procedure and, through a number of case studies, show the results from our citation data align well with our knowledge and intuition about these external topics. Overall, we have found that the statistical theory and methods recently invented by the statistics community have made increasing impact on other scientific fields.