Introduction To Meme Science

The meme (pronounced “mey mey”) is a subject of budding interdisciplinary study from the perspectives of evolutionary biology, epidemiology, complex network theory, sociology, and cultural theory. We will be sharing with you some examples of how each discipline approaches the problem of dank memes.

Here is a quick video from Olivia Gordon at SciShow to get you caught up on the history of the term “meme” in evolutionary biology and its relation to genetic reproduction, viruses, and culture:

While the term meme stems from this very evolutionary metaphor, there are a series of other approaches and perspectives that can add to and serve as a critique for the bio-centric meme theory.

Complex network theory has a lot to teach us about virality in networks. Network theory is a part of complex systems theory that models systems as a graph of nodes and connections between them. Just about any interconnected system of parts can be modelled as a network whether it be particle interactions, brain cells, telephone systems, sexual contact between people, or the spread of disease. Watts and Strogatz (1998) provided some key foundational work on network theory or “graph theory” which examined the properties of randomly connected graphs and what are called “small world networks” which are a system of hubs or interconnected clusters that have special information processing qualities. Here is a network theory video about contagion and diffusion that examines phenomena in terms of propagation, resistance, infectiousness, and strategy:

On the more quantitative side of things, Lilian Weng, associated with Filipo Menczer’s group at Indiana University, provides some insight on the information theoretic analysis of memes in terms of network connectivity, information diffusion and entropy. Here is a short video Dr. Weng explaining some of the findings:​​

See more of here wonderful work on predicting the virality of memes on her github site:

For the more post-modern oriented cultural studies and sociology folks, check out Tony Sampson’s 2012 theoretical work Virality: Contagion Theory in the Age of Networks. (A pdf copy of the text can be found here: Sampson's work is an exploration of social contagion in response to some giants of critical and social theory. This one might be a little tricky for those who haven't read their Foucault and Deleuze. He argues that virality is a primarily social phenomena that requires communities of discourse that have particular practices that allow for certain phenomena to spread. Here is a video breakdown of the text using some fun examples like Hipster culture and a breakdown of political and corporate hypnosis which causes the masses to 'sleepwalk through their existence':

Here is an interview with Tony Sampson about the 19th century social theorist Gabriel Tarde, his social contagion theory, and also Sampson’s use of Gille Deleuze’s work to reinterpret Tarde:

More meme science coming your way, but this should be enough to get you started!

Meme Science Bibliography

Albert, R., & Barabási, A. L. (2002). Statistical mechanics of complex networks. Reviews of modern physics, 74(1), 47.

Arbor, A., Romero, D. M., Uzzi, B., & Kleinberg, J. (2016). Social Networks Under Stress. Www2016, 9–20. (This is a fun one!)

Dorogovtsev, S. N., Goltsev, A. V., & Mendes, J. F. (2008). Critical phenomena in complex networks. Reviews of Modern Physics, 80(4), 1275.

Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. nature, 393(6684), 440.

Weng, L., Menczer, F., Ahn, Y.-Y. Y.-Y., Goffman, W., Newill, V. A., Daley, D. J., … Ugander, J. (2013). Virality Prediction and Community Structure in Social Networks. Scientific Reports, 3, 2522.

Weng, L. (2014). Information Diffusion on Online Social Networks, (April), 168.

Weng, L., Menczer, F., & Ahn, Y.-Y. (2014). Predicting Successful Memes using Network and Community Structure. arXiv Preprint arXiv:1403.6199, 10. Retrieved from

Weng, L., Menczer, F., Ahn, Y.-Y. Y.-Y., Goffman, W., Newill, V. A., Daley, D. J., … Ugander, J. (2013). Virality Prediction and Community Structure in Social Networks. Scientific Reports, 3, 2522.

Sampson, T. D. (2012). Virality: Contagion theory in the age of networks. U of Minnesota Press.

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