Understanding and predicting future research impact at different career stages—A social network perspective

Abstract

Performance assessment is ubiquitous and crucial in people analytics. Scientific impact, particularly, plays a significant role in the academia. This paper attempts to understand researchers' career trajectories by considering the research community as a social network, where individuals build ties with each other via coauthorship. The resulting linkage facilitates information flow and affects researchers' future impact. Consequently, we systematically investigate the career trajectories of researchers with respect to research impact using the social capital theory as our theoretical foundation. Specifically, for early‐stage and mid‐career academics, we find that connections with prominent researchers associate with greater impact. Brokerage positions, in addition, are beneficial to a researcher's research impact in the long run. For senior researchers, however, the only social network feature that significantly affects their future impact is the reputation of their recently built ties. Finally, we build predictive models on future research impact which can be leveraged by both organizations and individuals. This paper provides empirical evidence for how social networks provide signals on researchers' career dynamics guided by social capital theory. Our findings have implications for individual researchers to strategically plan and promote their careers and for research institutions to better evaluate current as well as prospective employees.

Exploring the clinical translation intensity of papers published by the world’s top scientists in basic medicine

“…In terms of the characteristics of authors, studies have shown that authors of different ages have different citation behaviors (Costas & Bordons, 2011 ; Costas et al, 2012 ). The physical age reflects the author’s career stage which has been found to affect scientific integrity (Fanelli et al, 2015 ), knowledge recency (Liang et al, 2020 ), work meaningfulness (Lopez & Ramos, 2017 ), future research impact (Zuo & Zhao, 2021 ), publication and scientists’ satisfaction (Husemann et al, 2017 ). Whether there are differences in clinical translation intensity in the papers published by authors at different career stages needs to be further examined.…”

Commentary on Highly Successful Female Educational Psychologists: Equity and Intersectionality in Success Definitions

“…This focus is a welcome and long overdue antidote to publication counts, which, although used by some hiring committees and science evaluators, have been repeatedly criticised by interdisciplinary and international scholars for being a poor certification of scientific merit (e.g. Trenchard, 1992;Feller, 2004;Zuo & Zhao, 2021). Prinz et al (2021) established the most successful female educational psychologists through an open call for nominations via social media of two key professional networks.…”

Evaluating BERT-based scientific relation classifiers for scholarly knowledge graph construction on digital library collections

“…One group includes metadata relations such as authorship, co-authorship, and citations [49,43]. Research in this group has focused mainly on examining the social dimension of scholarly communications, such as research impact assessments [36,40,18,10,12,34,46,56], co-author prediction [43,47,20,51,37] and scholarly community analysis [49]. Popular data resources that have been explored in this group include Microsoft Academic Graph [42] and PubMed [1].…”