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社交媒体分析

Social Media Analytics
课程网址: http://videolectures.net/single_leskovec_social/  
主讲教师: Jure Leskovec
开课单位: 斯坦福大学
开课时间: 2011-07-07
课程语种: 英语
中文简介:
在线社交媒体代表了信息生产、传输和消费方式的根本转变。本教程研究社交媒体建模、分析和优化的技术。首先介绍了大规模社会媒体数据的收集方法,然后讨论了处理和纠正数据丢失和不完整所带来的影响的技术。我们继续讨论在信息在用户之间传播时提取和跟踪信息的方法。然后,我们研究了提取时间模式的方法,通过这种模式,信息的普及率随着时间的推移而增长和衰退。我们展示了如何量化和最大化媒体渠道对特定内容的流行度和关注度的影响,以及如何建立信息传播和采用的预测模型。由于信息往往通过隐性社会和信息网络传播,我们提出了推断影响和扩散网络的方法。最后,我们讨论了通过网络跟踪情绪流动和出现两极分化的方法。
课程简介: Online social media represent a fundamental shift of how information is being produced, transferred and consumed. The present tutorial investigates techniques for social media modeling, analytics and optimization. First we present methods for collecting large scale social media data and then discuss techniques for coping with and correcting for the effects arising from missing and incomplete data. We proceed by discussing methods for extracting and tracking information as it spreads among the users. Then we examine methods for extracting temporal patterns by which information popularity grows and fades over time. We show how to quantify and maximize the influence of media outlets on the popularity and attention given to particular piece of content, and how to build predictive models of information diffusion and adoption. As the information often spreads through implicit social and information networks we present methods for inferring networks of influence and diffusion. Last, we discuss methods for tracking the flow of sentiment through networks and emergence of polarization. 
关 键 词: 计算机科学; 社交媒体; 扩散网络
课程来源: 视频讲座网
最后编审: 2021-12-23:liyy
阅读次数: 121