Independent Thinkers and Scientific Progress

An Analysis of Superstar Influence on Computer Science Research Dynamics

Bachelor thesis (2024)

Authors

F.J. Płonka Electrical Engineering, Mathematics and Computer Science

Contributors

H.S. Hung Pattern Recognition and Bioinformatics - EEMCS (mentor)
C. Hao Pattern Recognition and Bioinformatics - EEMCS (mentor)
V. Agarwal Pattern Recognition and Bioinformatics - EEMCS (mentor)
M. Khosla (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Published Date

25-06-2024

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In the scientific community, a few prominent researchers, known as "superstars," receive most of the attention, citations, and resources. However, it is unclear whether they promote true innovation. This study replicates and extends previous work analyzing how superstars influence their collaborators, focusing on the field of computer science. Using the Semantic Scholar Academic Graph dataset, we confirm that while connected researchers in computer science tend to publish more and receive more citations, their ideas are often less innovative. Unlike in the work we replicate, however, we observe this effect even before dissociating the connected researchers from superstars. We also develop a new metric to further clarify the impact of superstars on research diversity. The findings provide insights into the role of superstars in scientific innovation.