Recent advances in microblog content summarization has primarily viewed this task in the context of traditional multi-document summarization techniques where a microblog post or their collection form one document. While these techniques already facilitate information aggregation, categorization and visualization of microblog posts, they fall short in two aspects: i ) when summarizing a certain topic from microblog content, not all existing techniques take topic polarity into account. This is an important consideration in that the summarization of a topic should cover all aspects of the topic and hence taking polarity into account (sentiment) can lead to the inclusion of the less popular polarity in the summarization process. ii ) Some summarization techniques produce summaries at the topic level. However, it is possible that a given topic can have more than one important aspect that need to have representation in the summarization process. Our work in this paper addresses these two challenges by considering both topic sentiments and topic aspects in tandem. We compare our work with the state of the art Twitter summarization techniques and show that our method is able to outperform existing methods on standard metrics such as ROUGE-1.

中文翻译：

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推特的话题和情感感知微博摘要

微博内容摘要的最新进展主要是在传统的多文档摘要技术的背景下看待这项任务，其中微博帖子或其集合形成一个文档。虽然这些技术已经促进了微博帖子的信息聚合、分类和可视化，但它们在两个方面存在不足：i) 在从微博内容中总结某个主题时，并非所有现有技术都考虑了主题极性。这是一个重要的考虑因素，因为一个主题的摘要应涵盖该主题的所有方面，因此考虑到极性（情绪）可能会导致在摘要过程中包含不太受欢迎的极性。ii) 一些摘要技术在主题级别生成摘要。然而，一个给定的主题可能有不止一个需要在摘要过程中表示的重要方面。我们在本文中的工作通过同时考虑主题情绪和主题方面来解决这两个挑战。我们将我们的工作与最先进的 Twitter 摘要技术进行了比较，并表明我们的方法能够在标准指标（如 ROUGE-1）上优于现有方法。