论文标题
社交媒体的日益增长的放大：测量2009 - 2020年Twitter上150多种语言的时间和社会传染动态
The growing amplification of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020
论文作者
论文摘要
从2009年初到2019年底运行的1,180亿条消息的数据集工作，我们在Twitter上识别并探讨了150多种语言的相对日常使用。我们发现八种语言占所有推文的80％，英语，日语，西班牙语和葡萄牙语是最主要的。为了量化每种语言的社交传播，我们计算“传染比”：转发与有机信息的平衡。我们发现，对于Twitter上最常见的语言，转发而不是共享新内容的趋势越来越多，但并非普遍。到2019年底，包括英语和西班牙语在内的前30种语言中一半的传染比已经达到1-幼稚的传染阈值。在2019年，平均每日比率最高的前5种语言是泰式（7.3），印地语，泰米尔语，乌尔都语和加泰罗尼亚语，而最底层的5语言是俄罗斯，瑞典语，瑞典语，埃斯佩兰托，塞伯诺诺和芬兰人（0.26）。此外，我们表明，随着时间的流逝，大多数通用语言的传染率比稀有语言的传播比率更强。
Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. We find that eight languages comprise 80% of all tweets, with English, Japanese, Spanish, and Portuguese being the most dominant. To quantify social spreading in each language over time, we compute the 'contagion ratio': The balance of retweets to organic messages. We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content. By the end of 2019, the contagion ratios for half of the top 30 languages, including English and Spanish, had reached above 1 -- the naive contagion threshold. In 2019, the top 5 languages with the highest average daily ratios were, in order, Thai (7.3), Hindi, Tamil, Urdu, and Catalan, while the bottom 5 were Russian, Swedish, Esperanto, Cebuano, and Finnish (0.26). Further, we show that over time, the contagion ratios for most common languages are growing more strongly than those of rare languages.
