School of Liberal Arts, Xi'an University, Xi'an 710065, China.
Department of Liberal Arts, Guangdong University of Education, Guangzhou 510303, China.
Int J Environ Res Public Health. 2021 Sep 18;18(18):9850. doi: 10.3390/ijerph18189850.
The sudden appearance of a new epidemic disease in China created the need for names identifying that disease. Between December 2019 and January 2020, a variety of severe pneumonia-related disease names suddenly appeared, and more name varieties kept coming up afterwards. To better understand the introduction and spread of these names, 16 different COVID-19-related name varieties were selected covering the period from the end of December 2019, when the epidemic started, to mid-March 2020, a moment at which the term competition had stabilized. By way of big data analysis, the initiation and distribution of the 16 names across the media landscape was traced with regard to the impact of different media platforms, while the distribution frequency of each of the selected terms was mapped, resulting in a distinction of three groups of disease names, each with a different media and time profile. The results were discussed based on the hypotheses of disease confusion by name variety and management failures in absence of clear language governance at the national and global levels. The analysis of the data led to a refutation of both hypotheses. Based on this discussion, the study offers empirically based suggestions for the WHO in their naming practices and further research.
在中国突然出现一种新的传染病,需要给这种疾病起一个名称。在 2019 年 12 月至 2020 年 1 月期间,各种与严重肺炎相关的疾病名称突然出现,随后出现了更多的名称。为了更好地了解这些名称的引入和传播,选择了 16 种不同的与 COVID-19 相关的名称品种,涵盖了从 2019 年 12 月底疫情开始到 2020 年 3 月中旬的时期,此时术语竞争已经稳定。通过大数据分析,追踪了这 16 个名称在媒体领域的出现和分布情况,涉及不同媒体平台的影响,同时绘制了每个选定术语的分布频率,从而区分了三组疾病名称,每组具有不同的媒体和时间特征。根据国家和全球层面缺乏明确语言治理导致的名称多样性导致的疾病混乱和管理失败的假设,对结果进行了讨论。数据分析反驳了这两个假设。基于这一讨论,本研究为世界卫生组织在其命名实践和进一步研究方面提供了基于经验的建议。