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Keyword Selection Methodology for Identification of Major Events using Social Networks

机译：利用社交网络识别重大事件的关键词选择方法

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摘要

The understanding of information communicated over social networks enables quick tracking of real events as they occur. In other cases, where the "crowd" factor is on high note, it is possible to identify events and to evaluate their magnitude, even before they occur. A full assessment of the content generated by social network users is very complex. This, due to the gigantic volume of data communicated over the net at any given time. Using few, well defined, keywords for the detection of relevant data reduces, considerably, the processing effort and expedites the identification of events, such as wildfire, floods or terror attacks. The preliminary results here has shown that by using keywords, specially tailored for different types of major events, one may detect 'abnormal' surges of social network activities. Also, presented are threshold values, in terms of magnitude and frequency designed for early detection of these events. This approach is the basis for the development of algorithms for early identification real time systems and for geographical tracking of major events.
机译：对通过社交网络传达的信息的理解使得可以对真实事件进行快速跟踪。在其他情况下，“人群”因素非常重要，甚至在事件发生之前，就可以识别事件并评估其大小。对社交网络用户生成的内容的全面评估非常复杂。这是由于在任何给定时间通过网络传递的巨大数据量。使用很少的，定义明确的关键字来检测相关数据会大大减少处理工作，并加快对事件的识别，例如野火，洪水或恐怖袭击。初步结果表明，通过使用针对不同类型的重大事件量身定制的关键字，可以发现社交网络活动的“异常”激增。此外，还提供了针对幅度和频率的阈值，这些阈值是为早期检测这些事件而设计的。该方法是开发用于早期识别实时系统和对重大事件进行地理跟踪的算法的基础。

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