Dank or not? Analyzing and predicting the popularity of memes on Reddit.
COVID-19
Content-based analysis
Image analysis
Machine learning
Memes
Popularity prediction
Sentiment analysis
Social media
Visual humor
Journal
Applied network science
ISSN: 2364-8228
Titre abrégé: Appl Netw Sci
Pays: Switzerland
ID NLM: 101732938
Informations de publication
Date de publication:
2021
2021
Historique:
received:
13
10
2020
accepted:
02
02
2021
entrez:
15
3
2021
pubmed:
16
3
2021
medline:
16
3
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33718590
doi: 10.1007/s41109-021-00358-7
pii: 358
pmc: PMC7939928
doi:
Types de publication
Journal Article
Langues
eng
Pagination
21Informations de copyright
© The Author(s) 2021.
Déclaration de conflit d'intérêts
Competing interestsThe authors declare that they have no competing interests.
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