AMHERST, Mass. – Ten researchers at the University of Massachusetts Amherst have been recognized for being among the world’s most highly cited researchers in 2019 by London-based Clarivate Analytics, owner of the Web of Science.
Now in its sixth year, the citation analysis identifies influential researchers as determined by their peers around the world. They have consistently won recognition in the form of high citation counts over a decade. These scientists are judged to be influential, and their citation records are seen as “a mark of exceptional impact,” the company says.
The ten UMass Amherst researchers recognized on the 2019 list are Catrine Tudor-Locke and Laura Vandenberg of the School of Public Health and Health Sciences, food scientists David Julian McClements, Eric Decker and Hang Xiao, microbiologist Kelly Nevin and Derek Lovley, materials scientist Thomas Russell and chemist Vincent Rotello in the College of Natural Sciences, and environmental chemist Baoshan Xing of the Stockbridge School of Agriculture.
The list, announced this week from the company’s United States office in Philadelphia, contains about 3,400 highly cited researchers in science and social science fields. The company says it “focuses on contemporary research achievement: Only highly cited papers in science and social science journals indexed in the Web of Science Core Collection during the 11-year period 2008-2018 were surveyed.”
Last year for the first time, Highly Cited Researchers introduced a new cross- field category to identify researchers with substantial influence across several fields during the data census period. The most recent list names 6,216 researchers, 3,725 of them in specific fields and 2,491 for cross-field performance. This is the second year that researchers with cross-field impact have been identified.
As the report’s editors point out, “There is no unique or universally agreed concept of what constitutes extraordinary research performance and elite status in the sciences and social sciences. Consequently, no quantitative indicators will reveal a list that satisfies all expectations or requirements. Moreover, a different basis or formula for selection would generate a different – though likely overlapping – list of names. Thus, the absence of a name on our list cannot be interpreted as inferior performance or stature in comparison to those selected.”