| Summary: | 碩士 === 國立臺灣大學 === 資訊管理學研究所 === 97 === Since the 1990s, information markets have proved effective in predicting the outcome of public issues. A public issue is represented by an information market and all its possible outcomes form the contracts of the market. Through the mechanisms of market trading and rewarding, information markets are able to collect public’s opinions and convert the opinions into prices. The price of a contract indicates the feasibility of an outcome from public perspectives. High prices indicate that the public recognizes the outcome. By contrast, low prices mean that the outcome may not be feasible from the public’s viewpoint. The prices thus can help governments and policy makers establish reasonable policies to public issues. For each contract, we collect its price in a daily basis and propose a method to analyze the price sequence. We associate fluctuations in the price sequence with news documents and identify news events that cause the fluctuations. The identified events can help the public or social science scholars comprehend influential factors of public issues and social phenomena.
In the proposed approach, we first identify time periods accompanying significant price fluctuations. Next, we apply techniques of topic detection and tracking to cluster news documents in the periods. A cluster groups content-similar news documents and represents a news event. Finally, statistical feature selection methods are employed to identify events highly associated with the periods. The events then represent the cause of the price fluctuations and are influential to the corresponding public issue. Experiments based on a real world dataset demonstrate that the proposed method can identify influential events of information markets effectively. We also develop a prototype system based on the proposed method. The system graphically labels influential events of information markets that help users comprehend the development of public issues easily.
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