Abstract
Because of the mass growth of Internet popularity, and the quick spread of blogs in the recent years, blogs has become a civilian media with powerful influence. Several mechanisms have been developed for measuring, ranking, and searching blogs based on the different characteristics of blogs from original websites. On the other hand, the theory of prediction market has shown great abilities of predictions in business, organization managing, politics, and sports. This study proposes to implement a virtual stock market for valuing and ranking blogs. This study expects to reveal the relative value of listed blogs in the market by making transactions, and observes trading relationships among players by visualization tools. This study aims to implement a virtual stock market, and run two experiments with blogs and campus singing contest respectively, whose main purposes are testing, improving, and discussing the trading mechanism of the system. In order to identify the players who had profit by controlling multiple accounts, this study expects to find out suspicious trading behaviors by transforming target players’ transaction records into visualized trading relation networks. There are three conclusions of this study. First, it is workable to implement virtual stock market as a tool for blog recommendation and ranking, but it takes time to convince users to accept this new idea. Second, this study shows an extended ability of finding relative value of objects which is basically impossible to be quantified, such as the stock prices of singers. Third, this study shows that it is helpful to identify players with interest arbitrage in the experiment by drawing the trading relation networks.