The Possibility of an Epidemic Meme Analogy for Web Community Population Analysis

Kubo, Michinori; Naruse, Keitaro; Satō, Hiroshi; Matubara, Takashi

doi:10.1007/978-3-540-77226-2_107

Cited by 15 publications

(9 citation statements)

References 6 publications

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“…Intuition about how memes are created, transmitted, consumed, or mutated are often derived from their association with genes and the process of gene evolution [5] and more recently, memes have been considered through the lens of epidemiology and disease transmission [33,16]. Indeed, its etymology is a portmanteau of mind+gene, which begs the question: rather than continuing the economic analogy, are memes better situated in the realm of ecology?…”

Section: Introductionmentioning

confidence: 99%

Competition Dynamics in the Meme Ecosystem

Ford¹,

Krohn²,

Weninger³

2021

Preprint

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The creation and sharing of memes is a common modality of online social interactions. The goal of the present work is to better understand the collective dynamics of memes in this accelerating and competitive environment. By taking an ecological perspective and tracking the meme-text from 352 popular memes over the entirety of Reddit, we are able to show that the frequency of memes has scaled almost exactly with the total amount of content created over the past decade. This means that as more data is posted, an equal proportion of memes are posted. One consequence of limited human attention in the face of a growing number of memes is that the diversity of these memes has decreased at the community level, albeit slightly, in the same period. Another consequence is that the average lifespan of a meme has decreased dramatically, which is further evidence of an increase in competition and a decreasing collective attention span.

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Section: Introductionmentioning

confidence: 99%

Competition Dynamics in the Meme Ecosystem

Ford¹,

Krohn²,

Weninger³

2021

Preprint

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“…Wang and Wood used the SIR (sane–infected–recovery) contagion model, constituted by a non-linear system of three differential equations, to fitting meme propagation data found in Google Trends. The SIR model describes one of the most frequent dynamics recognized in meme spreading (Kubo et al , 2007) (Kermack and McKendrick, 1927), even before the internet era, so that it might be reasonable to test it also to identify meme origin not strictly connected to the Web.…”

Section: Methodsmentioning

confidence: 99%

Mechanisms of meme propagation in the mediasphere: a system dynamics model

Perissi

Falsini

Bardi

2019

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Purpose In the age of internet memes spread around the world in very short time, it has been already proved that, in several cases, the mechanism of propagation is very similar to a flu infection. However, this model turns out to be invalid if the spreading is generated by the mass media (TV, radio and the like). This paper aims to explore for the first time this non-viral dynamic (“fallout model”). Design/methodology/approach Two different dynamic models were developed to explain the viral and the mass media-powered meme propagations, and both were tested using data from Google Trends. Findings Viral propagation is not the only mechanism of meme diffusion. Memes can also diffuse by a “fallout” model, in which the susceptible populations are affected by the meme messages almost simultaneously, as it happens in the physical world for a radioactive fallout or for other poisoning agents. Originality/value This study provides a method to determine whether a certain meme has been diffusing by means of its own viral power or has been “planted” as the result of a commercial advertising campaign or a government propaganda operation.

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“…Their models are designed to characterize dynamics for both the communities and users. Article memes are studied by expressing complex human dynamics in analogy with infection by a virus [22]. These studies often assume the background environment as constant, which is not very practical in real world situations.…”

Section: Literature Reviewmentioning

confidence: 99%

A model-free scheme for meme ranking in social media

Zheng

Zeng

2016

Decision Support Systems

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The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, tags, etc.). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve this problem well. They are either daunted by unpractical assumptions or incapability of characterizing dynamic information. As such, in this paper, we elaborate a model-free scheme to rank online memes in the context of social media. This scheme is capable to characterize the nonlinear interactions of online users, which mark the process of meme diffusion. Empirical studies on two large-scale, real-world datasets (one in English and one in Chinese) demonstrate the effectiveness and robustness of the proposed scheme. In addition, due to its fine-grained modeling of user dynamics, this ranking scheme can also be utilized to explain meme popularity through the lens of social influence.

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The Possibility of an Epidemic Meme Analogy for Web Community Population Analysis

Cited by 15 publications

References 6 publications

Competition Dynamics in the Meme Ecosystem

Competition Dynamics in the Meme Ecosystem

Mechanisms of meme propagation in the mediasphere: a system dynamics model

A model-free scheme for meme ranking in social media

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