Literature DB >> 33718590

Dank or not? Analyzing and predicting the popularity of memes on Reddit.

Kate Barnes1,2, Tiernon Riesenmy1,3, Minh Duc Trinh1,4, Eli Lleshi1,5, Nóra Balogh1,6, Roland Molontay1,7,8.   

Abstract

Internet memes have become an increasingly pervasive form of contemporary social communication that attracted a lot of research interest recently. In this paper, we analyze the data of 129,326 memes collected from Reddit in the middle of March, 2020, when the most serious coronavirus restrictions were being introduced around the world. This article not only provides a looking glass into the thoughts of Internet users during the COVID-19 pandemic but we also perform a content-based predictive analysis of what makes a meme go viral. Using machine learning methods, we also study what incremental predictive power image related attributes have over textual attributes on meme popularity. We find that the success of a meme can be predicted based on its content alone moderately well, our best performing machine learning model predicts viral memes with AUC=0.68. We also find that both image related and textual attributes have significant incremental predictive power over each other.
© The Author(s) 2021.

Entities:  

Keywords:  COVID-19; Content-based analysis; Image analysis; Machine learning; Memes; Popularity prediction; Sentiment analysis; Social media; Visual humor

Year:  2021        PMID: 33718590      PMCID: PMC7939928          DOI: 10.1007/s41109-021-00358-7

Source DB:  PubMed          Journal:  Appl Netw Sci        ISSN: 2364-8228


  6 in total

1.  Competition-induced criticality in a model of meme popularity.

Authors:  James P Gleeson; Jonathan A Ward; Kevin P O'Sullivan; William T Lee
Journal:  Phys Rev Lett       Date:  2014-01-30       Impact factor: 9.161

2.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

3.  Competition among memes in a world with limited attention.

Authors:  L Weng; A Flammini; A Vespignani; F Menczer
Journal:  Sci Rep       Date:  2012-03-29       Impact factor: 4.379

4.  Gradient boosting machines, a tutorial.

Authors:  Alexey Natekin; Alois Knoll
Journal:  Front Neurorobot       Date:  2013-12-04       Impact factor: 2.650

5.  Average is boring: how similarity kills a meme's success.

Authors:  Michele Coscia
Journal:  Sci Rep       Date:  2014-09-26       Impact factor: 4.379

Review 6.  Convolutional neural networks: an overview and application in radiology.

Authors:  Rikiya Yamashita; Mizuho Nishio; Richard Kinh Gian Do; Kaori Togashi
Journal:  Insights Imaging       Date:  2018-06-22
  6 in total
  1 in total

1.  COVID-19 in Memes: The Adaptive Response of Societies to the Pandemic?

Authors:  Piotr Skórka; Beata Grzywacz; Dawid Moroń; Magdalena Lenda
Journal:  Int J Environ Res Public Health       Date:  2022-10-10       Impact factor: 4.614

  1 in total

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