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The Science of Science: Big Data, Metrics, and Impact

ΣΥΓΓΡΑΦΕΙΣ
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This is the first comprehensive overview of the 'science of science,' an emerging interdisciplinary field that relies on big data to unveil the reproducible patterns that govern individual scientific careers and the workings of science. It explores the roots of scientific impact, the role of productivity and creativity, when and what kind of collaborations are effective, the impact of failure and success in a scientific career, and what metrics can tell us about the fundamental workings of science. The book relies on data to draw actionable insights, which can be applied by individuals to further their career or decision makers to enhance the role of science in society. With anecdotes and detailed, easy-to-follow explanations of the research, this book is accessible to all scientists and graduate students, policymakers, and administrators with an interest in the wider scientific enterprise.

  •  
  • The first comprehensive book in the field of the science of science
  • Provides strategies for enhancing careers and working productively across all scientific disciplines
  • Examines areas of the science of science ripe for further study and research
Συγγραφείς: Barabasi Albert-Laszlo, Wang Dashun
Εκδότης: CAMBRIDGE UNIVERSITY PRESS
Σελίδες: 308
ISBN: 9781108716956
Εξώφυλλο: Μαλακό Εξώφυλλο
Αριθμός Έκδοσης: 1
Έτος έκδοσης: 2021

Introduction
Part I. The Science of Career:
1. Productivity of a scientist
2. The H Index
3. The Matthew Effect
4. Age and Scientific Achievement
5. Random Impact Rule
6. The Q Factor
7. Hot Streaks
Part II. The Science of Collaboration:
8. The increasing dominance of teams in science
9. The Invisible College
10. Coauthorship Networks
11. Team Assembly
12. Small and large teams
13. Scientific Credit
14. Credit Allocation
Part III. The Science of Impact:
15. Big Science
16. Citation Disparity
17. High Impact Papers
18. Scientific Impact
19. The Time Dimension of Science
20. Ultimate Impact
Part IV. Outlook:
21. Can Science be Accelerated?
22. Artificial Intelligence
23. Bias and Causality in Science
Part V. Last thought
All the Science of Science: Appendix A1 Modeling team assembly
Appendix A2 Modeling Citations
References
Index.

Albert-László Barabási is Robert Gray Dodge Professor of Network Science and Distinguished University Professor at Northeastern University, Boston, where he directs the Center for Complex Network Research. He holds appointments in the Departments of Physics and the College of Computer and Information Science, as well as in the Department of Medicine at Harvard Medical School and at Brigham and Women Hospital in the Channing Division of Network Science.

Dashun Wang is an Associate Professor at Kellogg School of Management and the founding director of the Center for Science of Science and Innovation, Northwestern University, Illinois. He is a recipient of the AFOSR Young Investigator Award and was named Poets and Quants Best 40 Under 40 Business School Professors in 2019.

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