Modeling and Predicting Individual Scientific Impact

Abstract

We accomplished several important findings in the third year (from Feb 1, 2019, to Jan 31, 2020). First, we discovered the mechanisms that govern the dynamics of failures, which was published in Nature. In this paper, we develop a simple one parameter model that mimics how successful future attempts build on past efforts. Solving this model analytically suggests that a phase transition separates the dynamics of failure into regions of progression or stagnation. Our second finding about the early-career setback was published in Nature Communications. We analyzed junior scientists whose proposals that fell just below and just above the funding threshold. Although near-miss significantly increases attrition in NIH system, individuals with near misses systematically outperform those with narrow wins in the longer run. Third, we discovered the mechanisms governing the dynamics of the substitutive system for subjects ranging from mobile handsets to automobiles and from smartphone apps to scientific fields. We find that early growth patterns follow a power law with non-integer exponents and uncover three generic ingredients governing substitutions. This paper has been published in Nature Human Behavior. Lastly, we curated a novel dataset on the career profiles of near all Nobel Laureates and published this dataset in Scientific Data. We analyzed this dataset and find that apart from their prize-winning work, the careers of Nobel laureates follow the same patterns as those of the majority of scientists. The result has been published in Nature Review Physics.

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Document Details

Document Type
Technical Report
Publication Date
Aug 19, 2020
Accession Number
AD1107183

Entities

People

  • Dashun Wang

Organizations

  • Northwestern University

Tags

Communities of Interest

  • Biomedical
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Artificial Intelligence
  • Big Data
  • Commerce
  • Data Mining
  • Data Science
  • Department Of Defense
  • Human Behavior
  • Information Science
  • Knowledge Management
  • Leadership
  • Mathematics
  • Network Science
  • Personal Information Managers
  • Personnel Management
  • Phase Transformations
  • Physics
  • Public Policy
  • Schools
  • Scientific Research
  • Social Media
  • Social Sciences
  • Symposia
  • Training
  • Trajectories
  • Universities

Fields of Study

  • Physics

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development
  • Military History of the United States in the 20th Century.