Being able to automatically extract as much relevant posts as possible from social media in a timely manner is key in many activities, for example to provide useful information in order to rapidly create crisis maps during emergency events. While most social media support keyword-based searches, the amount and the accuracy of retrieved posts depend largely on the keywords employed. The goal of the proposed methodology is to dynamically extract relevant keywords for searching social media during an emergency event, following the event’s evolution. Starting from a set of keywords designed for the type of event being considered (floods and earthquakes, in particular), the set of keywords is automatically adjusted taking into account the spatio-temporal features of the monitored event. The goal is to retrieve posts following the event’s evolution and to benefit from cross-social crawling in order to exploit the specific characteristics of a social media over others. In the case considered in this paper, we exploit the precision of the geolocation of images posted in Flickr to extract keywords to search YouTube posts for the same event, since YouTube does not allow spatial crawling yet provides a richer source of information. The methodology was evaluated on three recent major emergency events, demonstrating a large increase in the number of retrieved posts compared with the use of generic seed keywords. This is a relevant improvement of relevance for providing information on emergency events, and the ability to follow the event’s development.

中文翻译：

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社交媒体在紧急事件中跨社会爬网的关键词时空挖掘

能够及时从社交媒体上自动提取尽可能多的相关帖子是许多活动的关键，例如，提供有用的信息以便在紧急事件期间快速创建危机图。尽管大多数社交媒体都支持基于关键字的搜索，但是检索到的帖子的数量和准确性很大程度上取决于所使用的关键字。所提出的方法的目标是随着事件的发展动态地提取相关关键词以在紧急事件期间搜索社交媒体。从针对所考虑事件类型（尤其是洪水和地震）设计的一组关键字开始，考虑到受监视事件的时空特征，自动调整该组关键字。目标是在事件的发展过程中检索帖子，并从跨社交爬网中受益，以便利用社交媒体的其他特征。在本文考虑的情况下，我们利用Flickr中发布的图像的地理位置精确度来提取关键字，以搜索同一事件的YouTube帖子，因为YouTube不允许空间抓取，但提供了更丰富的信息源。在最近的三起重大紧急事件中对该方法进行了评估，表明与使用通用种子关键字相比，检索到的职位数量大大增加。这是在提供有关紧急事件信息的相关性方面的重要改进，并且可以跟踪事件的发展。