As the COVID-19 pandemic continues its march around the world, an unprecedented amount of open data is being generated for genetics and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated in the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique world-wide event into biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 152 million tweets, growing daily, related to COVID-19 chatter generated from January 1st to April 4th at the time of writing. This open dataset will allow researchers to conduct a number of research projects relating to the emotional and mental responses to social distancing measures, the identification of sources of misinformation, and the stratified measurement of sentiment towards the pandemic in near real time.
Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-19
Crisis-induced differences in attention towards Ukraine in Twitter 2008-2023
Tallinn University（塔林大学）；Estonian Literary Museum（爱沙尼亚文学博物馆）；Baltic Film, Media and Arts School, Tallinn University（塔林大学波罗的海电影、媒体与艺术学院）；Vermont Complex Systems Institute（佛蒙特复杂系统研究所）；University of Vermont（佛蒙特大学）；Santa Fe Institute（圣塔菲研究所）；Complexity Science Hub（复杂性科学中心）
Country Image in COVID-19 Pandemic: A Case Study of China
School of Journalism and Communication, Tsinghua University（清华大学新闻与传播学院）；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）
Empathy and Hope: Resource Transfer to Model Inter-country Social Media Dynamics
持续的COVID-19大流行对国际关系造成重大影响，包括旅行限制、全球停火以及国际疫苗生产和共享协议。在印度的感染浪潮导致医疗基础设施系统性崩溃之际，一个总部设在巴基斯坦的社会福利组织提出采购医用级氧气，以帮助印度-一个在过去几十年中与巴基斯坦发生四次战争的国家。在本文中，我们关注巴基斯坦Twitter用户对印度持续医疗危机的反应。虽然#IndiaNeedsOxygen和#PakistanStandsWithIndia是巴基斯坦最热门的标签之一，但#EndiaSaySorryToKashmir等分裂性标签同时开始流行。在包括四场战争在内的有争议的历史背景下，这种性质的分裂内容，特别是当一个国家面临前所未有的医疗危机时，会进一步恶化关系。在本文中，我们定义了一个新的任务，检测\emph{supportive}的内容，并证明现有的\emph{NLP for social impact}工具可以有效地利用这些任务在一个快速的周转时间。我们还发布了第一个公开可用的数据集，在地缘政治关系和印度和巴基斯坦肆虐的流行病的背景下。
The University of Tokyo（东京大学）；Barcelona Supercomputing Center（巴塞罗那超级计算中心）；Yale University（耶鲁大学）；Preferred Networks, inc.（Preferred Networks公司）；Tokyo Institute of Technology（东京工业大学）；Tokyo Medical and Dental University（东京医科齿科大学）；ESSEC Business School（埃塞克商学院）；Tokyo Metropolitan Hospital（东京都立医院）；Janssen Pharmaceutical（杨森制药）；Kantar（凯度）；SUSTech（南方科技大学）
