# Inheritance patterns in citation networks reveal scientific memes

arXiv: https://arxiv.org/abs/1404.3757 · HTML: https://mlsanity.com/paper/1404.3757/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2014.

## Built on by (most cited first, 2 of 2)

- [Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation](https://mlsanity.com/paper/2312.12881/) (2023)
- [What We Talk About When We Talk About LMs: Implicit Paradigm Shifts and the Ship of Language Models](https://mlsanity.com/paper/2407.01929/) (2024)

## Abstract (arXiv)

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.