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

ABSTRACT: Statistical methodologies are indispensable in data-driven scientific discoveries. In this paper, we make the first effort to understand the impact of recent statistical innovations on other scientific fields. 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, and we find increasing citation diversity. Furthermore, in a new setting, we apply a local clustering technique involving personalized PageRank with graph conductance for size selection to find the most relevant statistical innovation for a given external topic in other fields. Through a number of case studies, we show that the results from our citation data analysis align well with our knowle

SUBMITTER: Wang L 

PROVIDER: S-EPMC9403407 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature