Tobias Kuhn (Author), Matjaž Perc (Author), Dirk Helbing (Author)

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 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.

Keywords

memi;dedovanje;geni;teorija mrež;kompleksni sistemi;memes;inheritance;genes;network science;complex systems;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM FNM - Faculty of Natural Sciences and Mathematics
UDC: 53
COBISS: 20976904 Link will open in a new window
ISSN: 2160-3308
Views: 1426
Downloads: 421
Average score: 0 (0 votes)
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Other data

Secondary language: Slovenian
Secondary keywords: memi;dedovanje;geni;teorija mrež;kompleksni sistemi;
URN: URN:SI:UM:
Type (COBISS): Article
Pages: str. 041036-1-041036-9
Volume: ǂVol. ǂ4
Issue: ǂiss. ǂ4
Chronology: 2014
DOI: 10.1103/PhysRevX.4.041036
ID: 10851686