博客传播动态是否与股市活动相关?

M. Choudhury, H. Sundaram, A. John, D. Seligmann
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引用次数: 140

摘要

在本文中,我们开发了一个简单的模型来研究和分析博客圈中的交流动态,并使用这些动态来确定与股票市场运动的有趣相关性。这项工作可以推动网络上的定向广告,也有助于理解博客圈中的社区演变。我们通过几个简单的通信上下文属性来描述通信动态,例如帖子的数量,评论的数量,评论的长度和响应时间,评论的强度以及人们可以获得的不同信息角色(早期响应者/后期响应者,忠诚者/异常值)。我们研究了一个名为Engadget (http://www.engadget.com)的“精通技术”的社区。本文有两个关键贡献:(a)我们确定了四家科技公司的信息角色和上下文属性,(b)我们将它们建模为支持向量机框架中的回归问题,并用公司的股票运动训练模型。有趣的是,博客圈的交流活动与股市走势有相当大的相关性。这些相关措施进一步交叉验证了两种基线方法。我们的结果很有希望,在预测运动幅度和运动方向方面的准确率分别为78%和87%。
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Can blog communication dynamics be correlated with stock market activity?
In this paper, we develop a simple model to study and analyze communication dynamics in the blogosphere and use these dynamics to determine interesting correlations with stock market movement. This work can drive targeted advertising on the web as well as facilitate understanding community evolution in the blogosphere. We describe the communication dynamics by several simple contextual properties of communication, e.g. the number of posts, the number of comments, the length and response time of comments, strength of comments and the different information roles that can be acquired by people (early responders / late trailers, loyals / outliers). We study a "technology-savvy" community called Engadget (http://www.engadget.com). There are two key contributions in this paper: (a) we identify information roles and the contextual properties for four technology companies, and (b) we model them as a regression problem in a Support Vector Machine framework and train the model with stock movements of the companies. It is interestingly observed that the communication activity on the blogosphere has considerable correlations with stock market movement. These correlation measures are further cross-validated against two baseline methods. Our results are promising yielding about 78% accuracy in predicting the magnitude of movement and 87% for the direction of movement.
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