Human-network-based filtering: the information propagation model based on word-of-mouth communication

In the real world, people get filtered information through word-of-mouth communication. This type of information is "filtered" because the information from one user to another is filtered by the people who pass the information to other people. We propose an Information Propagation Model, which simulates word-of-mouth communication on a computer network. In this model, certain information of interest to a user is automatically distributed to neighboring users. Therefore, this model works as an information filtering system filtered by a human network. In this paper we describe the concepts of this model, the features found in this model, and the preliminary experiment, which was carried out by real users. Results of the experiment show both the effectiveness of filtering in our model, and also that the value of information correlates closely with the distance from which the information was transferred.