Start Date
12-16-2013
Description
How are scholars ranked for promotion, tenure and honors? How can we improve the quantitative tools available for decision makers when making such decisions? Current academic decisions are mostly very subjective. In the era of “Big Data,” a solid quantitative set of measurements should be used to support this decision process. This paper presents a method for predicting the probability of a paper being in the most cited papers using only data available at the time of publication. We find that structural network properties are associated with increased odds of being in the top percentile of citation count. The paper also presents a method for predicting the future impact of researchers, using information available early in their careers. This model integrates information about changes in a young researcher’s role in the citation network and co-authorship network and demonstrates how this improves predictions of their future impact.
Recommended Citation
Bertsimas, Dimitris; Brynjolfsson, Erik; Reichman, Shachar; and Silberhoz, John, "Network Analysis for Predicting Academic Impact" (2013). ICIS 2013 Proceedings. 92.
https://aisel.aisnet.org/icis2013/proceedings/ResearchInProgress/92
Network Analysis for Predicting Academic Impact
How are scholars ranked for promotion, tenure and honors? How can we improve the quantitative tools available for decision makers when making such decisions? Current academic decisions are mostly very subjective. In the era of “Big Data,” a solid quantitative set of measurements should be used to support this decision process. This paper presents a method for predicting the probability of a paper being in the most cited papers using only data available at the time of publication. We find that structural network properties are associated with increased odds of being in the top percentile of citation count. The paper also presents a method for predicting the future impact of researchers, using information available early in their careers. This model integrates information about changes in a young researcher’s role in the citation network and co-authorship network and demonstrates how this improves predictions of their future impact.