Department of History and Philosophy of Science, University of Pittsburgh, Pittsburgh, PA, United States of America.
Department of Computer Science, University of Colorado, Boulder, CO, United States of America.
PLoS One. 2019 May 23;14(5):e0216922. doi: 10.1371/journal.pone.0216922. eCollection 2019.
This work examines Twitter discussion surrounding the 2015 outbreak of Zika, a virus that is most often mild but has been associated with serious birth defects and neurological syndromes. We introduce and analyze a collection of 3.9 million tweets mentioning Zika geolocated to North and South America, where the virus is most prevalent. Using a multilingual topic model, we automatically identify and extract the key topics of discussion across the dataset in English, Spanish, and Portuguese. We examine the variation in Twitter activity across time and location, finding that rises in activity tend to follow to major events, and geographic rates of Zika-related discussion are moderately correlated with Zika incidence (ρ = .398).
本研究考察了 2015 年寨卡病毒爆发期间的推特讨论,这种病毒通常症状较轻,但与严重的出生缺陷和神经系统综合征有关。我们介绍并分析了一个包含 390 万条提到寨卡病毒的推文的数据集,这些推文的地理位置位于病毒最为流行的北美和南美。我们使用多语言主题模型,自动识别并提取了英语、西班牙语和葡萄牙语数据集中的关键讨论主题。我们考察了时间和地点上的推特活动变化,发现活动的增加往往与重大事件有关,寨卡相关讨论的地理分布与寨卡发病率(ρ=0.398)有中度相关性。