Discovering information diffusion paths from blogosphere for online advertising

ABSTRACT

Allowing global distribution of information to large audiences at very low cost, the Internet has emerged as a vital medium for marketing and advertising. Weblogs, a new form of self publication on the Internet, have attracted online advertisers because of their incredible growth-rate in recent years. In this paper, we propose to discover information diffusion paths from the blogosphere to track how information frequently flows from blog to blog. This knowledge can be used in various applications of online campaign. Our approach is based on analyzing the content of blogs. After detecting trackable topics of blogs, we model a blog community as a blog sequence database. Then, the discovery of information diffusion paths is formalized as a problem of frequent pattern mining. We develop a new data mining algorithm to discover information diffusion paths. Experiments conducted on real life dataset show that our algorithm discovers information diffusion paths efficiently. The discovered information diffusion paths are accurate in predicting the future information flow in the blog community.

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Index Terms

• Information systems

  • Information retrieval

    • Evaluation of retrieval results

      • Relevance assessment