arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2011.14326cs.SIcs.CLcs.CVcs.CYphysics.soc-ph
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Dank or Not? -- Analyzing and Predicting the Popularity of Memes on Reddit

Aquincum Institute of Technology(阿昆库姆理工学院);Colorado College(科罗拉多学院);University of Kansas(堪萨斯大学);Haverford College(哈弗福德学院);Tufts University(塔夫茨大学);Dmlab Ltd.(Dmlab有限公司);MTA-BME Stochastics Research Group(MTA-BME随机研究组);Budapest University of Technology and Economics(布达佩斯技术与经济大学)

Kate Barnes, Tiernon Riesenmy, Minh Duc Trinh, Eli Lleshi, Nóra Balogh, Roland Molontay

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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