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推特是关于什么的?公共事件和Twitter订阅源之间的主题关联

What Were the Tweets About? Topical Associations between Public Events and Twitter Feeds
课程网址: http://videolectures.net/icwsm2012_hu_twitter/  
主讲教师: Yuheng Hu
开课单位: 伊利诺大学
开课时间: 2012-07-06
课程语种: 英语
中文简介:
像Twitter这样的社交媒体渠道已经成为群众响应公众和电视事件(如演讲和辩论)的平台。然而,非常大量的响应为尝试从中提取感觉提出了挑战。在这项工作中,我们提出了一种基于事件和相关Twitter提要的主题影响的联合统计建模的分析方法。该模型使事件的自动分割和推文的表征分为两类:(1)特定响应事件片段内容的情节性推文,以及(2)通常响应事件的稳定推文。通过将我们的方法应用于两组大型推文以响应2011年5月奥巴马总统关于中东的讲话以及2011年9月的共和党初选辩论,我们将介绍这些推文的内容。我们还在时间轴上揭示了事件对推文的影响的性质和程度。在用户研究中,我们进一步表明,与现有技术相比,用户发现通过我们的方法发现的主题和情节推文具有更高的质量和更有趣,并且在18 41%的范围内进行了改进。
课程简介: Social media channels such as Twitter have emerged as platforms for crowds to respond to public and televised events such as speeches and debates. However, the very large volume of responses presents challenges for attempts to extract sense from them. In this work, we present an analytical method based on joint statistical modeling of topical influences from the events and associated Twitter feeds. The model enables the auto-segmentation of the events and the characterization of tweets into two categories: (1) episodic tweets that respond specifically to the content in the segmentsof the events, and (2) steady tweets that respond generally about the events. By applying our method to two large sets of tweets in response to President Obama's speech on the Middle East in May 2011 and a Republican Primary debate in September 2011, we present what these tweets were about. We also reveal the nature and magnitude of the influences of the event on the tweets over its timeline. In a user study, we further show that users find the topics and the episodic tweets discovered by our method to be of higher quality and more interesting as compared to the state-of-the-art, with improvements in the range of 18-41%.
关 键 词: 社交媒体; 情节性推文; 联合统计建模
课程来源: 视频讲座网
最后编审: 2020-07-16:yumf
阅读次数: 38