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Kermanshah Earthquake Event Tracking Through Persian Tweets

机译:Kermanshah地震事件通过波斯推文跟踪

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By expanding online social networks during the last decade, online event tracking has become one of the vital issues among researchers. In this study, Persian tweets which exchange among Iranian users have been considered in order to track hidden patterns of evolutionary Kermanshah earthquake event. A well-known dynamic community detection algorithm has been applied over key-graphs which are generated from extracted keywords of tweets. The key-graphs are generated from KNTUPT dataset which consists of entire Persian tweets between November 24th, 2017 and December 8th, 2017. The experimental study reveals the dynamic community detection algorithm had a superior result in terms of modularity as community quality and execution time as performance.
机译:通过在过去十年中扩展在线社交网络,在线事件跟踪已成为研究人员之间的重要问题之一。在这项研究中,波斯推文已经考虑了伊朗用户之间的交换,以便跟踪进化的克尔曼哈地震事件的隐藏模式。众所周知的动态群落检测算法已应用于从提取的推文的提取关键字生成的键图。关键图是从kntupt dataSet生成的,该数据集由11月24日之间的整个波斯推文组成 th ,2017年和12月8日 th 在2017年。实验研究揭示了动态社区检测算法在模块化方面具有优异的结果,作为社区质量和执行时间作为性能。

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