Self-organization of progress across the century of physics

Abstract

We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalization.

5 two-column pages, 5 figures; accepted for publication in Scientific Reports [the n-gram viewer for publications of the American Physical Society is available at http://www.matjazperc.com/aps]

References in corpus (6)

• Power-law distributions in empirical data
• World citation and collaboration networks: uncovering the role of geography in science
• Evolution of the most common English words and phrases over the centuries
• Universality, limits and predictability of gold-medal performances at the Olympic Games
• In science "there is no bad publicity": Papers criticized in comments have high scientific impact
• Identifying trends in word frequency dynamics

Cited by in corpus (19)

• Statistical physics of human cooperation
• The Matthew effect in empirical data
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• History of art paintings through the lens of entropy and complexity
• Interacting discovery processes on complex networks
• Inheritance patterns in citation networks reveal scientific memes
• Rank diversity of languages: Generic behavior in computational linguistics
• Science and Facebook: the same popularity law!
• Impact of lexical and sentiment factors on the popularity of scientific papers
• Rank dynamics of word usage at multiple scales
• Modeling the coevolution between citations and coauthorships in scientific papers
• Using Machine Learning to Predict the Evolution of Physics Research
• Dynamics of senses of new physics discourse: co-keywords analysis
• A generalized voter model with time-decaying memory on a multilayer network
• Effect of Burstiness on the Air Transportation System
• Phase transitions in a decentralized graph-based approach to human language
• A minor extension of the logistic equation for growth of word counts on online media: Parametric description of diversity of growth phenomena in society
• Worldwide bilateral geopolitical interactions network inferred from national disciplinary profiles
• Mapping the changing structure of science through diachronic periodical embeddings