大数据时代的计算政治学研究

Computational Political Science in the Era of Big Data

政治学研究一直是社会科学领域的热点研究方向。政治理论、比较政治、公共政策和国际政治等,这些经典的政治学研究课题吸引了大批的政治学学者。从传统政治学研究中的道德哲学和法理主义,到行为主义政治学研究中的科学方法论和定量分析,再到一些自然科学工作者开始涉足政治学领域,政治学的研究方法一直在发展与演变。该文在对传统政治学研究的方法进行简要总结的基础上,针对互联网时代,"大数据"驱动下的政治学研究,阐述了计算政治学的起源、定义及其主要的研究内容和方法,论述了目前研究的热点政治倾向性及政治观点识别、冲突观点检测、选举预测和分析可视化的研究进展。

The study of politics has been a hot research spot in the field of social science, such as political theory, comparative politics, public policy, and international politics. From the moral philosophy and legal theory in the traditional politics, to the scientific methodology and quantitative analysis in behavioristic politics, further to the involvement of natural science researchers, the research methods in politics have been developing and evolving. After a brief summary of previous methods in political science research, this paper discusses the origin, definition and development of computational political science at the age of the Internet, especially in the era of big data. It reviews the progress of political orientation, opinion recognition, conflict point detection, election prediction and political analysis visualization.