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EVENT FORECASTING THROUGH NEWS SENTIMENT ANALYSIS
MPhil Thesis Defence Title: "EVENT FORECASTING THROUGH NEWS SENTIMENT ANALYSIS" By Mr. Yancheng Hong Abstract Forecasting is the process of making statements about events whose actual outcomes have not yet been observed. Accurate forecasting will help people making right decision and thus save time and effort for the society. Recently, there are more and more efforts put into designing sophisticated models to improve forecasting accuracy. There are time series models, qualitative models, and causal models. The techniques have been advanced from simple regression to multiple regression, from moving average to trend analysis. A number of assertions have been made that more sophisticated models yield better forecasting results. In this thesis, we tried to improve our forecasting accuracy by incorporating the sentiment analysis data. We showed that the forecasting for sports betting and political events can be significantly improved by using sentiment analysis as a pre-processor. The reason is that the sentiment data is generated from a wide-covered news sources and can be viewed as an aggregation of a very large group of people. As argued by The Wisdom of Crowds, decision draw from aggregation of information in groups are often better than those could have been made by any single member of the group. We also showed that with sentiment analysis data, even simple intuitive models, like linear regression model and regression model with exponentially weighted moving average technique, can generate better results. We also further derived profitable strategies for sports betting and accurate forecasting for political events. As a result, our experimental results also validated our sentiment analysis system em Lydia. We hope further investigation of the usage of sentiment data in forecasting can be performed in different areas, like national economical data forecasting, most popular product forecasting, and even Oscar awardee forecasting. Date: Wednesday, 30 June 2010 Time: 2:00pm – 4:00pm Venue: Room 4483 Lifts 25/26 Committee Members: Prof. Mordecai Golin (Supervisor) Prof. Steven Skiena (Supervisor) Prof. Dit-Yan Yeung (Chairperson) Dr. Ke Yi **** ALL are Welcome ****