The understanding of global social pattern can benefit the society operation a lot, including the domestic social governance, international situation awareness, risk assessment and forecasting, conflict resolution, crisis response and future policy planning. As the development of Internet, hundreds of millions of news could be found online every day, reporting the social events around the world, including political events, diplomatic events, cultural events, natural disasters, etc. However, by manual reading and analyzing, it is too difficult to deal with the vast amount of data and obtain valuable information quickly. Thus, in this paper we investigate the global social event extraction and analysis method based on the automatic processing of online news, including 1) event model building, 2) event information extraction and automatic classification based on English news text, 3) global social dynamic analysis and visualization based on event data. Finally, we constructed the method on the real global news data collected from more than 200 sites
to evaluate their performance and interpret some underlying insights of the results.