Abstract—Even though blog contents vary a lot in quality, the disclosure of personal opinions and the huge blogging population always attracts marketing’s attention on blog information. In this paper, we investigate how marketers can identify the information propagation in degree among blog communities. In this way, topic similarity, relatedness, and word repetition between leader and followers’ writing products are considered as the propagated information. The contribution of this paper is twofold. The work presented here is to show how blog content can be economically and feasibly analyzed by existing internet sources such as Wikipedia database and the usage of page return from a Japanese search engine. To this extent, this system, which combined in-link algorithms and text mining analyzes, tracing propagation channels and propagateable information allows analyzing the power of influences in viral marketing. We demonstrated the effectiveness of the system by applying blogger identification, topic identification, and the topic propagations.

Index Terms—blog, text mining, viral marketing, content based propagation, Wikipedia, thesaurus, page return of search engine  

Cite: Meichieh Chen, Neil Rubens, Fumihiko Anma, Toshio Okamoto, "Monitoring Propagations in the Blogosphere for Viral Marketing," Journal of Emerging Technologies in Web Intelligence, Vol. 4, No. 1, pp. 94-105, February 2012. doi:10.4304/jetwi.4.1.94-105