2014/04/30 by Tobias Kuhn, Matjaz Perc, Matjaž Perc +1 · 3 citations
Computer Science · Physics and Astronomy · Social Sciences · #Evolutionary Game Theory and Cooperation #Language and cultural evolution #Wikis in Education and Collaboration #cs.DL #cs.SI #physics.soc-ph
paper · pdf · doi:10.1103/physrevx.4.041036
published as Phys. Rev. X 4 (2014) 041036 · 8 two-column pages, 5 figures; accepted for publication in Physical Review X
arxiv created 2014/10/25 · openalex publication_date 2014/11/21 · arxiv updated 2014/11/25 · openalex created_date 2020/11/23 · openalex updated_date 2026/07/28
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.