Background

Since the World Health Organization (WHO) declared the COVID-19 as a Public Health Emergency of International Concern (PHEIC) on January 31, 2020, governments have been enfaced with crisis for timely responses. The efficacy of these responses directly depends on the social behaviors of the target society. People react to these actions with respect to the information they received from different channels, such as news and social networks. Thus, analyzing news demonstrates a brief view of the information users received during the outbreak.

Methods

The raw data used in this study is collected from official news channels of news wires and agencies in Telegram messenger, which exceeds 2,400,000 posts. The posts that are quoted by NCRC’s members are collected, cleaned, and divided into sentences. The topic modeling and tracking are utilized in a two-stage framework, which is customized for this problem to separate miscellaneous sentences from those presenting concerns. The first stage is fed with embedding vectors of sentences where they are grouped by the Mapper algorithm. Sentences belonging to singleton nodes are labeled as miscellaneous sentences. The remained sentences are vectorized, adopting Tf-IDF weighting schema in the second stage and topically modeled by the LDA method. Finally, relevant topics are aligned to the list of policies and actions, named topic themes, that are set up by the NCRC.

Results

Our results show that major concerns presented in about half of the sentences are (1) PCR lab. test, diagnosis, and screening, (2) Closure of the education system, and (3) awareness actions about washing hands and facial mask usage. Among the eight themes, intra-provincial travel and traffic restrictions, as well as briefing the national and provincial status, are under-presented. The timeline of concerns annotated by the preventive actions illustrates the changes in concerns addressed by NCRC. This timeline shows that although the announcements and public responses are not lagged behind the events, but cannot be considered as timely. Furthermore, the fluctuating series of concerns reveal that the NCRC has not a long-time response map, and members react to the closest announced policy/act.

Conclusion

The results of our study can be used as a quantitative indicator for evaluating the availability of an on-time public response of Iran’s NCRC during the first three months of the outbreak. Moreover, it can be used in comparative studies to investigate the differences between awareness acts in various countries. Results of our customized-design framework showed that about one-third of the discussions of the NCRC’s members cover miscellaneous topics that must be removed from the data.

中文翻译：

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使用两阶段无监督主题建模跟踪伊朗国家 COVID-19 响应委员会的主要关注点

背景

自世界卫生组织 (WHO) 于 2020 年 1 月 31 日宣布 COVID-19 为国际关注的突发公共卫生事件 (PHEIC) 以来，各国政府一直面临着危机，需要及时应对。这些反应的效果直接取决于目标社会的社会行为。人们根据从不同渠道（例如新闻和社交网络）收到的信息对这些行为做出反应。因此，分析新闻展示了用户在爆发期间收到的信息的简要视图。

方法

本研究中使用的原始数据来自 Telegram messenger 中的新闻通讯社和机构的官方新闻频道，超过 2,400,000 个帖子。NCRC成员引用的帖子被收集，清理并分成句子。主题建模和跟踪在一个两阶段框架中使用，该框架针对此问题进行了定制，以将杂句与提出问题的句子分开。第一阶段输入句子的嵌入向量，它们由 Mapper 算法分组。属于单例节点的句子被标记为杂句。剩下的句子被向量化，在第二阶段采用 Tf-IDF 加权模式，并通过 LDA 方法进行局部建模。最后，相关主题与政策和行动列表保持一致，命名为主题主题，

结果

我们的结果表明，大约一半的句子中提出的主要问题是（1）PCR 实验室。测试、诊断和筛查，（2）关闭教育系统，以及（3）关于洗手和面膜使用的宣传行动。在八个主题中，省内旅行和交通限制以及国家和省级情况的介绍不足。预防措施标注的关注点时间表说明了 NCRC 解决的关注点的变化。这条时间线表明，虽然公告和公众反应并不落后于事件，但不能被认为是及时的。此外，波动的一系列担忧表明，NCRC 没有长期响应地图，成员对最接近的宣布政策/法案做出反应。

结论

我们的研究结果可作为量化指标，用于评估伊朗 NCRC 在疫情爆发的前三个月内能否及时做出公共反应。此外，它可以用于比较研究，以调查不同国家的意识行为之间的差异。我们定制设计框架的结果表明，NCRC 成员的讨论中约有三分之一涉及必须从数据中删除的杂项主题。