Generating timeline summaries with social media attention

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• 作者：Wayne Xin Zhao ; Ji-Rong Wen ; Xiaoming Li
• 刊名：Frontiers of Computer Science in China
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：10
• 期：4
• 页码：702-716
• 全文大小：679 KB
• 刊物类别：Computer Science
• 刊物主题：Computer Science, general
  Chinese Library of Science
  
• 出版者：Higher Education Press, co-published with Springer-Verlag GmbH
• ISSN：1673-7466
• 卷排序：10

文摘

Timeline generation is an important research task which can help users to have a quick understanding of the overall evolution of one given topic. Previous methods simply split the time span into fixed, equal time intervals without studying the role of the evolutionary patterns of the underlying topic in timeline generation. In addition, few of these methods take users’ collective interests into considerations to generate timelines.We consider utilizing social media attention to address these two problems due to the facts: 1) social media is an important pool of real users’ collective interests; 2) the information cascades generated in it might be good indicators for boundaries of topic phases. Employing Twitter as a basis, we propose to incorporate topic phases and user’s collective interests which are learnt from social media into a unified timeline generation algorithm.We construct both one informativeness-oriented and three interestingness-oriented evaluation sets over five topics.We demonstrate that it is very effective to generate both informative and interesting timelines. In addition, our idea naturally leads to a novel presentation of timelines, i.e., phase based timelines, which can potentially improve user experience.Keywordstimelinesocial media attentionphaseusers’ collective interests