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SEA: A System for Event Analysis on Chinese Tweets

机译:SEA:中文推文事件分析系统

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摘要

Recent years have witnessed the explosive growth of online social media. Weibo, a famous "Chinese Twitter", has attracted over 0.5 billion users in less than four years, with more than 1000 tweets generated in every second. These tweets are informative but very fragmented, and thus would be better archived from an event perspective, as done by Weibo itself in the "Micro-Topic" program. This effort, however, is yet far from satisfaction for not providing enough analytical power to events. In light of this, in this demo paper, we propose SEA, a System for Event Analysis on Chinese tweets. In general, SEA is an event-centric, multi-functional platform that conducts panoramic analysis on Weibo events from various aspects, including the semantic information of the events, the temporal and spatial trends, the public sentiments, the hidden sub-events, the key users in the event diffusion and their preferences, etc. These functions are enabled by the integration of various analytical models and by the NoSQL techniques adopted purposefully for massive tweets management. Finally, a case study on the "Spring Festival" event demonstrates the effectiveness of SEA. To our best knowledge, SEA is the first third-party system that provides panoramic analysis to Weibo events.
机译:近年来见证了在线社交媒体的爆炸性增长。微博是著名的“中国推特”,在不到四年的时间里已经吸引了超过5亿用户,每秒产生1000条以上的推文。这些推文内容丰富,但非常零散,因此,从事件的角度来看,可以更好地进行存档,就像微博本身在“微主题”程序中所做的那样。但是,由于没有为事件提供足够的分析能力,因此这项工作还远远不能令人满意。有鉴于此,在本演示文件中,我们提出了SEA,一种用于中文推文的事件分析系统。一般而言,SEA是一个以事件为中心的多功能平台,它从各个方面对微博事件进行全景分析,包括事件的语义信息,时空趋势,公众情绪,隐藏的子事件,事件扩散及其偏好等方面的关键用户。这些功能通过各种分析模型的集成以及通过专门用于大规模推文管理的NoSQL技术而启用。最后,以“春节”活动为例的案例证明了SEA的有效性。据我们所知,SEA是第一个提供对微博事件进行全景分析的第三方系统。

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