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Learning in Twitter Streams with 280 Character Tweets

机译:在Twitter流中学习,具有280个字符的推文

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摘要

Social networks are a thriving source of information and applications are pervasive. Twitter has recently experienced a significant change in its essence with the doubling of the number of maximum allowed characters from 140 to 280. In this work we study the changes that come from such modification when learning systems are in place. Results on real datasets of both settings show that transferring models between both scenarios may need special treatment, as bigger tweets are harder to classify, making such dynamic environments even more challenging.
机译:社交网络是一个蓬勃发展的信息来源,应用程序是普遍存在的。 Twitter最近经历了一个重要的变化,其本质上具有从140到280到280的最大允许字符的倍增。在这项工作中,我们研究了在学习系统到位时这种修改的变化。结果两种设置的实际数据集显示,两种情况之间的传输模型可能需要特殊处理,因为更大的推文更难分类,使得这种动态环境更具挑战性。

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