論文

In this paper, we attempt to specify the influencer and the influential terms in consumer package goods by using the influence diffusion model (IDM). IDM calculates the spread of a term in the blogosphere recursively, and evaluates the influence of terms, blog entries, and bloggers. The model was applied to the official data from a blog hosting service. The results of the model were compared with the term frequency (TF). Then, the influencers of the IDM were examined and compared with the results of other network indices such as number of links and trackbacks. The results indicate that IDM performs better in finding blogs posted by bloggers with product usage experience or with an interest in the product. A propagation network which visualizes the consumer-oriented key marketing elements is also presented. An empirical analysis suggests the validity of IDM for marketing decision marking.

Several attempts have been made to analyze information diffusion on online knowledge sharing sites. In this poster, we report a preliminary study analyzing @cosme, a viral marketing site, which is among the largest community sites in Japan. The notable characteristics of @cosme are that users can bookmark their favorite reviewers; moreover, they can post their own reviews of products. In other words, a user puts trust in some other users for their reviews. This trust relation affects the opinions of users: A user refers to the ratings and opinions from the user's own favorite users when purchasing products; some users come to be trusted by a user based on mutual similarities of ratings and opinions. This bidirectional interaction between trust and opinion is an important phenomenon that elucidates consumer behaviors in online communities. In this paper, we describe an overview of the data in @cosme, analyses of recommendation through the trust relation, and concept for future analyses.