Inheritance patterns in citation networks reveal scientific memes
arXiv:1404.3757 · doi:10.1103/PhysRevX.4.041036
Abstract
Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and we validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.
8 two-column pages, 5 figures; accepted for publication in Physical Review X
References in corpus (5)
- Universality of citation distributions: towards an objective measure of scientific impact
- Diffusion of scientific credits and the ranking of scientists
- World citation and collaboration networks: uncovering the role of geography in science
- Principles of scientific research team formation and evolution
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Cited by in corpus (5)
- The Aging Effect in Evolving Scientific Citation Networks
- Stochastic dynamics and the predictability of big hits in online videos
- A model for meme popularity growth in social networking systems based on biological principle and human interest dynamics
- Effect of Burstiness on the Air Transportation System
- How the fittest compete for leadership: A tale of tails