The use of the LastQuake information system, its app, the associated Twitter account, and, to a lesser extent, the EMSC’s websites have been analyzed for the 7 days following the November 26, 2019, M6.4 Albania destructive earthquake to evaluate what can be improved and how crowdsourcing of information and monitoring of both use and absence of use of the app can contribute to rapid situational awareness. The mainshock and its numerous felt aftershocks triggered a strong public desire for information, which in turn led to rapid and massive adoption of the LastQuake app by up to 5% of the country’s population. The constant flow of new app users created a stress test of the app’s crowdsourcing features and led to errors in the association of felt reports with their appropriate earthquake. However, these errors had no identifiable impact, supporting the conclusion that the curation mechanisms currently in place are efficient. The rapid succession of felt aftershocks contributed to these errors by making information related to the mainshock difficult to access within hours of its occurrence, especially for new users who were not attuned to the app, since more recent events pushed older ones down the timeline of presented information. This revealed that prioritization of information within the app layout was lacking and must be an important design objective, especially during aftershock sequences. LastQuake has been shown to be a powerful tool for rapid situational awareness. The possibility of damage was detected within 8 min of the mainshock earthquake by a lack of LastQuake app activity close to the epicenter. This possibility was then gradually strengthened as new data became available and was finally confirmed by the reception of the first geo-located pictures of structural damage and building collapse within 60–70 min. Direct exchanges on Twitter were appreciated by eyewitnesses and seemed to help to reduce their anxiety in some cases (based on the personal reports). Questions mainly focused on the possible evolution of the seismicity. Attempts to debunk prediction claims were difficult. We report on how this could be eased and possibly made more efficient by sharing among the different actors a clear, concise, pre-prepared statement in the local language, that explains the state of scientific knowledge and the difference between prediction, early warning, or forecasts.

在2019年11月26日阿尔巴尼亚M6.4破坏性地震之后的7天里，对LastQuake信息系统，其应用程序，相关的Twitter帐户以及在较小范围内的EMSC网站的使用进行了分析，以评估进行改进，以及如何对信息进行众包以及对应用程序的使用和不使用的监视可以促进快速的态势感知。主震及其产生的余震引发了公众对信息的强烈渴望，进而导致该国多达5％的人口迅速大量采用LastQuake应用程序。新应用程序用户的不断涌入对应用程序的众包功能进行了压力测试，并导致毛毡报告与适当地震之间的关联出现错误。但是，这些错误没有明显的影响，支持当前有效的策展机制有效的结论。感觉到的余震的快速连续性，使得与主震有关的信息在其发生后数小时内难以访问，尤其是对于那些不熟悉该应用的新用户，因为较新的事件将较旧的事件推向了所提出的时间表，导致了这些错误。信息。这表明在应用程序布局中缺乏信息优先级，这必须是重要的设计目标，尤其是在余震序列期间。事实证明，LastQuake是快速了解情况的强大工具。由于震源附近缺少LastQuake应用程序活动，因此在主震地震发生8分钟内检测到了损坏的可能性。随着新数据的获得，这种可能性逐渐增强，并最终在60-70分钟内收到第一张关于结构破坏和建筑物倒塌的地理位置图片，从而证实了这一可能性。目击者赞赏在Twitter上进行直接交流，这在某些情况下（根据个人报告）似乎有助于减轻他们的焦虑感。问题主要集中在地震活动的可能演变上。试图揭穿预测的主张很困难。我们报告了如何通过在不同参与者之间共享以本地语言表达的清晰，简洁，预先准备好的陈述来缓解这种情况，并可能提高效率，该陈述解释了科学知识的状态以及预测，预警或预测。