Simulating the spatial diffusion of memes on social media networks

Dang, Lanxue; Chen, Zhuo; Lee, Jay; Tsou, Ming‐Hsiang; Ye, Xinyue

doi:10.1080/13658816.2019.1591414

Cited by 23 publications

(13 citation statements)

References 36 publications

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“…Earlier we mentioned an empirical study of human Internet memes that concluded geography was still important. [12] It is not clear at the moment how evolutionary pressure might have brought this about. Perhaps it is simply a holdover or from unknown causes.…”

Section: Meme-meme Competition Backgroundmentioning

confidence: 99%

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A Theoretical Treatment of Memetic Traits Using Gene-Meme, Meme-Meme and Population Equilibrium

Shuler¹

2021

Preprint

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Background: Conceived as a unit of lasting cultural (mostly vertical) trait transmission, memes now include transient horizontally transmitted fads. Memes may sometimes follow the logic of population genetics, e.g. learned birdsong, but not always over the diverse range found in human hosts. Much current work focuses on selection of memes rather than hosts. Methods: We analyze equilibrium between gene-meme and meme-meme competing propagators and consider whether a meme is linked to reproduction (e.g. vertical culture transmission), or not. We employ a genetic component and combined meme induced fitness components for hosts, while memes have replication factors to distinguish from what’s good for the host (fitness). To anticipate future meme effects on population stability we use a Monte Carlo simulation roughly calibrated to the Industrial Revolution. Results: A basic effective calculus of memetic trait competition and interaction with genes is derived and analyzed. The transient nature of short term memes may be a defense against accumulation of deleterious memes. Horizontally transmitted (panmictic) memes with high spreading rate will often not equalize with a genetic trait, spreading outside of natural selection of the hosts, presenting a cumulative existential threat. Vertical transmission reduces replication rate and allows group selection against deleterious memes. Competing mutually exclusive memes contribute to inequality and altruism, but compete through adverse fitness since exclusivity assumes low conversion. Conclusions: The advantage of a portfolio of groups or species may not accrue to a single group. This analytical understanding elevates meme-risk to the level of a candidate solution to the so-called Fermi Paradox, as interstellar travel might require a planet wide group.

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Section: Meme-meme Competition Backgroundmentioning

confidence: 99%

“…But, as recently as 2019 it was reported that geography, even in the Internet age, is still important in transmission of Internet memes. [12] Lynch and Baker concluded from an analysis of birdsong memes that increased variability in memetic transmission support "high levels of among-population differentiation . .…”

Section: Introductionmentioning

confidence: 99%

A Theoretical Treatment of Memetic Traits Using Gene-Meme, Meme-Meme and Population Equilibrium

Shuler¹

2021

Preprint

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“…The transitions among different states are modeled by differential equations. In contrast, agent-based models [2,4,8] have considered the heterogeneity of agents. They simulate the diffusion in realistic networks by defining how the infection may occur through individual-based interactions (e.g., infection can only occur when agents are at the same location).…”

Section: Related Workmentioning

confidence: 99%

Stand

Desmarais

Peuquet

2020

Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation

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Information, ideas, and diseases, or more generally, contagions, spread over time and space through individual transmissions via social networks, as well as through external sources. A detailed picture of any diffusion process can be achieved only when both a detailed network structure and individual diffusion pathways are obtained. Studying such diffusion networks provides valuable insights to understand important actors in carrying and spreading contagions and to help predict occurrences of new infections. Most prior research focuses on modeling diffusion process only in the temporal dimension. The advent of rich social, media and geotagged data now allows us to study and model this diffusion process in both temporal and spatial dimensions than previously possible. Nevertheless, how information, ideas or diseases are propagated through the network as an overall spatiotemporal process is difficult to trace. This propagation is continuous over time and space, where individual transmissions occur at different rates via complex and latent connections. To tackle this challenge, a probabilistic spatiotemporal algorithm for network diffusion simulation (STAND) is developed based on the survival model in this research. Both time and geographic distance are used as explanatory variables to simulate the diffusion process over two different network structures. The aim is to provide a more detailed measure of how different contagions are transmitted through various networks where nodes denote geographic locations at a large scale. CCS CONCEPTS • Theory of computation → Network flows; • Computing methodologies → Network science.

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“…But, as recently as 2019 it was found that geography is still important in transmission of Internet memes. [14] Lynch and Baker concluded from an analysis of birdsong memes that increased variability in memetic transmission support "high levels of among-population differentiation . .…”

Section: Introductionmentioning

confidence: 99%

A Theoretical Treatment of Memetic Traits Using Gene-Meme, Meme-Meme and Population Equilibrium

Shuler¹

2021

Preprint

View full text Add to dashboard Cite

Background: The term meme includes vertical trait transmission and laterally transmitted ideas that can be lasting or transient. Memes may sometimes follow the logic of population genetics, e.g. learned birdsong, but not when laterally transmitted. Much current work focuses on selection of memes rather than hosts. This paper investigates mathematically the interaction of behaviorally transmitted traits with host selection fitness. Methods: We analyze equilibrium between gene-meme and meme-meme competing propagators and consider whether a meme is linked to reproduction (e.g. vertical culture transmission), or not. We employ a genetic component and combined meme-induced fitness components for hosts, while memes have replication factors to distinguish from what’s good for the host (fitness). We use a Monte Carlo simulation roughly calibrated to the Industrial Revolution to study meme effects on population stability. Results: A basic effective calculus of memetic trait competition and interaction with genes is derived and analyzed. The transient nature of many lateral memes may be a defense against accumulation of deleterious memes. Laterally transmitted (panmictic) memes with high spreading rate will often not equalize with a genetic trait, spreading outside of natural selection of the hosts, presenting a cumulative existential threat. Vertical transmission reduces replication rate and allows group selection against deleterious memes. Competing mutually exclusive memes contribute to inequality and altruism, but compete through adverse fitness since exclusivity assumes low conversion. Conclusions: The advantage of a portfolio of groups or species may not accrue to a single group. This understanding elevates meme-risk to the level of a candidate solution to the so-called Fermi Paradox.

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Simulating the spatial diffusion of memes on social media networks

Cited by 23 publications

References 36 publications

A Theoretical Treatment of Memetic Traits Using Gene-Meme, Meme-Meme and Population Equilibrium

A Theoretical Treatment of Memetic Traits Using Gene-Meme, Meme-Meme and Population Equilibrium

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A Theoretical Treatment of Memetic Traits Using Gene-Meme, Meme-Meme and Population Equilibrium

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