论文标题
还是不是潮湿？ - 分析和预测模因在Reddit上的普及
Dank or Not? -- Analyzing and Predicting the Popularity of Memes on Reddit
论文作者
论文摘要
互联网模因已成为当代社会交流的一种越来越普遍的形式，最近引起了很多研究的兴趣。在本文中，我们分析了2020年3月中旬从Reddit收集的129,326个模因的数据，当时世界各地正在引入最严重的冠状病毒限制。本文不仅为Covid-19大流行期间的互联网用户的思想提供了一个外观的玻璃，而且我们还对模因传播的原因进行了基于内容的预测分析。使用机器学习方法，我们还研究了哪些相关的预测能力图像与模因受欢迎程度有关的文本属性具有哪些相关的属性。我们发现，模因的成功可以基于其内容中等地预测，我们最佳性能的机器学习模型可以预测AUC = 0.68的病毒模因。我们还发现，与图像相关的属性和文本属性彼此具有显着的增量预测能力。
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.
