面向商业智能的新兴主题检测：“模因”动态的预测分析
Toward Emerging Topic Detection for Business Intelligence: Predictive Analysis of `Meme' Dynamics
摘要：
通过分析互联网数据来检测和表征新兴的讨论主题和消费者趋势对企业来说非常感兴趣。本文考虑的问题，监测网络发现新兴的模因-独特的短语，作为“示踪剂”的主题-作为一种手段，早期发现新的主题和趋势。我们提出了一种新的方法来预测哪些模因将广泛传播，出现在数百或数千篇博客文章中，哪些不会，从而能够发现重要的主题。我们首先确定应该预测模因成功的可测量指标。有趣的是，这些指标不是传统上用于这种预测的指标，而是对模因动态的微妙测量。这些指标构成了学习分类器的基础，该分类器可以预测给定的模因是否会广泛传播。预测方法的效用是通过分析2008年下半年出现在网上的模因来证明的。
英文摘要：
Detecting and characterizing emerging topics of discussion and consumer trends through analysis of Internet data is of great interest to businesses. This paper considers the problem of monitoring the Web to spot emerging memes - distinctive phrases which act as "tracers" for topics - as a means of early detection of new topics and trends. We present a novel methodology for predicting which memes will propagate widely, appearing in hundreds or thousands of blog posts, and which will not, thereby enabling discovery of significant topics. We begin by identifying measurables which should be predictive of meme success. Interestingly, these metrics are not those traditionally used for such prediction but instead are subtle measures of meme dynamics. These metrics form the basis for learning a classifier which predicts, for a given meme, whether or not it will propagate widely. The utility of the prediction methodology is demonstrated through analysis of memes that emerged online during the second half of 2008.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
