Background: A substantial amount of COVID-19–related data is generated by Twitter users every day. Self-reports of COVID-19 symptoms on Twitter can reveal a great deal about the disease and its prevalence in the community. In particular, self-reports can be used as a valuable resource to learn more about common symptoms and whether their order of appearance differs among different groups in the community. These data may be used to develop a COVID-19 risk assessment system that is tailored toward a specific group of people. Objective: The aim of this study was to identify the most common symptoms reported by patients with COVID-19, as well as the order of symptom appearance, by examining tweets in Arabic. Methods: We searched Twitter posts in Arabic for personal reports of COVID-19 symptoms from March 1 to May 27, 2020. We identified 463 Arabic users who had tweeted about testing positive for COVID-19 and extracted the symptoms they associated with the disease. Furthermore, we asked them directly via personal messaging to rank the appearance of the first 3 symptoms they had experienced immediately before (or after) their COVID-19 diagnosis. Finally, we tracked their Twitter timeline to identify additional symptoms that were mentioned within ±5 days from the day of the first tweet on their COVID-19 diagnosis. In total, 270 COVID-19 self-reports were collected, and symptoms were (at least partially) ranked. Results: The collected self-reports contained 893 symptoms from 201 (74%) male and 69 (26%) female Twitter users. The majority (n=270, 82%) of the tracked users were living in Saudi Arabia (n=125, 46%) and Kuwait (n=98, 36%). Furthermore, 13% (n=36) of the collected reports were from asymptomatic individuals. Of the 234 users with symptoms, 66% (n=180) provided a chronological order of appearance for at least 3 symptoms. Fever (n=139, 59%), headache (n=101, 43%), and anosmia (n=91, 39%) were the top 3 symptoms mentioned in the self-reports. Additionally, 28% (n=65) reported that their COVID-19 experience started with a fever, 15% (n=34) with a headache, and 12% (n=28) with anosmia. Of the 110 symptomatic cases from Saudi Arabia, the most common 3 symptoms were fever (n=65, 59%), anosmia (n=46, 42%), and headache (n=42, 38%). Conclusions: This study identified the most common symptoms of COVID-19 from tweets in Arabic. These symptoms can be further analyzed in clinical settings and may be incorporated into a real-time COVID-19 risk estimator.

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中文翻译：

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从阿拉伯语推文中识别常见的 COVID-19 症状并对其进行排名：内容分析

背景：Twitter 用户每天都会生成大量与 COVID-19 相关的数据。在 Twitter 上自我报告 COVID-19 症状可以揭示有关该疾病及其在社区中流行情况的大量信息。特别是，自我报告可以作为宝贵的资源来更多地了解常见症状以及社区中不同群体的症状出现顺序是否不同。这些数据可用于开发针对特定人群的 COVID-19 风险评估系统。目的：本研究的目的是通过检查阿拉伯语推文来确定 COVID-19 患者报告的最常见症状以及症状出现的顺序。方法：我们搜索了阿拉伯语 Twitter 帖子，寻找 2020 年 3 月 1 日至 5 月 27 日期间有关 COVID-19 症状的个人报告。我们识别了 463 名曾在 Twitter 上发布过关于 COVID-19 检测呈阳性的阿拉伯用户，并提取了他们与该疾病相关的症状。此外，我们通过个人消息直接要求他们对他们在诊断出 COVID-19 之前（或之后）出现的前 3 种症状进行排名。最后，我们跟踪了他们的 Twitter 时间线，以识别自首次发布有关 COVID-19 诊断的推文之日起 ±5 天内提到的其他症状。总共收集了 270 份 COVID-19 自我报告，并对症状进行了（至少部分）排名。结果：收集到的自我报告包含来自 201 名 (74%) 男性和 69 名 (26%) 女性 Twitter 用户的 893 种症状。大多数（n=270，82%）被跟踪用户居住在沙特阿拉伯（n=125，46%）和科威特（n=98，36%）。此外，收集到的报告中有 13% (n=36) 来自无症状个体。在 234 名有症状的用户中，66% (n=180) 提供了至少 3 种症状出现的时间顺序。自我报告中提到的前 3 个症状是发烧（n=139，59%）、头痛（n=101，43%）和嗅觉丧失（n=91，39%）。此外，28% (n=65) 的受访者表示，他们的 COVID-19 经历始于发烧，15% (n=34) 的受访者表示头痛，12% (n=28) 的受访者表示嗅觉缺失。在来自沙特阿拉伯的 110 例有症状病例中，最常见的 3 种症状是发烧（n=65，59%）、嗅觉丧失（n=46，42%）和头痛（n=42，38%）。结论：这项研究从阿拉伯语推文中确定了 COVID-19 最常见的症状。这些症状可以在临床环境中进一步分析，并可能纳入实时 COVID-19 风险估计器中。

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