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.
翻译:在本文中,我们分析了在2020年3月中旬从Reddit收集的129 326个Memes的数据,当时世界各地正在引入最严重的冠状病毒限制。这一条不仅为在COVID-19大流行期间互联网用户的想法提供了一个审视的玻璃,而且我们还对是什么使Meme病毒传播了基于内容的预测性分析。我们使用机器学习方法,还研究了哪些与预测力图像相关的递增属性超过Meme流行的文字属性。我们发现,光凭其内容即可预测Meme的成功,我们最有效果的机器学习模型预测了AUC=0.68的病毒模式。我们还发现,与图像有关的和文字属性对彼此具有重要的递增预测力。