Generating timeline summaries with social media attention  

作　　者：Wayne Xin ZHAO Ji-Rong WEN Xiaoming LI 

机构地区：[1]School of Information, Renmin University of China, Beijing 100872, China [2]Beijing Key Laboratory of Big Data Management and Analysis Methods, Renmin University of China, Beijing 100872, China [3]School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China [4]Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, Beijing 100144, China

出　　处：《Frontiers of Computer Science》2016年第4期702-716,共15页中国计算机科学前沿（英文版）

摘　　要：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 presen- tation of timelines, i.e., phase based timelines, which can potentially improve user experience.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 presen- tation of timelines, i.e., phase based timelines, which can potentially improve user experience.

关 键 词：TIMELINE social media attention phase users＇collective interests 

分 类 号：TU18[建筑科学—建筑理论] G212[文化科学—新闻学]