Entropy and complexity unveil the landscape of memes evolution

Abstract On the Internet, information circulates fast and widely, and the form of content adapts to comply with users’ cognitive abilities. Memes are an emerging aspect of the internet system of signification, and their visual schemes evolve by adapting to a heterogeneous context. A fundamental ques...

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Autores principales:	Carlo M. Valensise, Alessandra Serra, Alessandro Galeazzi, Gabriele Etta, Matteo Cinelli, Walter Quattrociocchi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f6ebae4a3a9d4341ab57067e96f8ddfb
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spelling	oai:doaj.org-article:f6ebae4a3a9d4341ab57067e96f8ddfb2021-12-02T16:57:08ZEntropy and complexity unveil the landscape of memes evolution10.1038/s41598-021-99468-62045-2322https://doaj.org/article/f6ebae4a3a9d4341ab57067e96f8ddfb2021-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-99468-6https://doaj.org/toc/2045-2322Abstract On the Internet, information circulates fast and widely, and the form of content adapts to comply with users’ cognitive abilities. Memes are an emerging aspect of the internet system of signification, and their visual schemes evolve by adapting to a heterogeneous context. A fundamental question is whether they present culturally and temporally transcendent characteristics in their organizing principles. In this work, we study the evolution of 2 million visual memes published on Reddit over ten years, from 2011 to 2020, in terms of their statistical complexity and entropy. A combination of a deep neural network and a clustering algorithm is used to group memes according to the underlying templates. The grouping of memes is the cornerstone to trace the growth curve of these objects. We observe an exponential growth of the number of new created templates with a doubling time of approximately 6 months, and find that long-lasting templates are associated with strong early adoption. Notably, the creation of new memes is accompanied with an increased visual complexity of memes content, in a continuous effort to represent social trends and attitudes, that parallels a trend observed also in painting art.Carlo M. ValensiseAlessandra SerraAlessandro GaleazziGabriele EttaMatteo CinelliWalter QuattrociocchiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Carlo M. Valensise Alessandra Serra Alessandro Galeazzi Gabriele Etta Matteo Cinelli Walter Quattrociocchi Entropy and complexity unveil the landscape of memes evolution
description	Abstract On the Internet, information circulates fast and widely, and the form of content adapts to comply with users’ cognitive abilities. Memes are an emerging aspect of the internet system of signification, and their visual schemes evolve by adapting to a heterogeneous context. A fundamental question is whether they present culturally and temporally transcendent characteristics in their organizing principles. In this work, we study the evolution of 2 million visual memes published on Reddit over ten years, from 2011 to 2020, in terms of their statistical complexity and entropy. A combination of a deep neural network and a clustering algorithm is used to group memes according to the underlying templates. The grouping of memes is the cornerstone to trace the growth curve of these objects. We observe an exponential growth of the number of new created templates with a doubling time of approximately 6 months, and find that long-lasting templates are associated with strong early adoption. Notably, the creation of new memes is accompanied with an increased visual complexity of memes content, in a continuous effort to represent social trends and attitudes, that parallels a trend observed also in painting art.
format	article
author	Carlo M. Valensise Alessandra Serra Alessandro Galeazzi Gabriele Etta Matteo Cinelli Walter Quattrociocchi
author_facet	Carlo M. Valensise Alessandra Serra Alessandro Galeazzi Gabriele Etta Matteo Cinelli Walter Quattrociocchi
author_sort	Carlo M. Valensise
title	Entropy and complexity unveil the landscape of memes evolution
title_short	Entropy and complexity unveil the landscape of memes evolution
title_full	Entropy and complexity unveil the landscape of memes evolution
title_fullStr	Entropy and complexity unveil the landscape of memes evolution
title_full_unstemmed	Entropy and complexity unveil the landscape of memes evolution
title_sort	entropy and complexity unveil the landscape of memes evolution
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f6ebae4a3a9d4341ab57067e96f8ddfb
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Entropy and complexity unveil the landscape of memes evolution

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