Identification of Promising Researchers through Fast-and-frugal Heuristics

Predicting a researcher’s future scientific achievements is essential for selection committees. Due to the unreflective use of metrics in evaluation processes, committees have to take controversial decisions while guiding exclusively by such metrics. This paper proposes a novel fast-and-frugal heuristics approach to identify prematurely prominent researchers. This study analyzes the careers of 1,631 computer scientists from ACM data set used as applicants in our selection models. We compared the percentages of these applicants who had been successfully chosen by future promise-based heuristics and traditional-indicators-based heuristics. We founded that estimated future performance-based heuristics are more reliable than traditional-indicators-based heuristics.

Authors and Affiliations

1. Department of Informatics, Federal University of Maranhão, São Luís, MA, Brazil

   Antônio de Abreu Batista-Jr

2. Oswaldo Cruz Foundation, House of Oswaldo Cruz, Museum of Life, Rio de Janeiro, RJ, Brazil

   Fábio Castro Gouveia

3. Center for Mathematics, Computation and Cognition, Federal University of ABC, Santo André, SP, Brazil

   Jesús P. Mena-Chalco

Corresponding author

Correspondence to Antônio de Abreu Batista-Jr .

Editors and Affiliations

1. Open University of Cyprus, Nicosia, Cyprus

   Yannis Manolopoulos

2. Information Management Systems Institute, Marousi, Greece

   Thanasis Vergoulis

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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