社会科学大数据计算——大数据时代计算社会科学的核心议题

Big Data Computing of Social Science:The Key Topics of Computational Social Science in Big Data Era

大数据时代的数据累积与技术进步,为计算社会科学的发展奠定了新的契机,大数据计算也取代社会模拟成为计算社会科学的核心议题。社会科学大数据计算,依托最新的大数据分析处理技术,致力于从符合社会研究需要的数据海洋中挖掘、清洗出有价值的"知识数据",并在此基础上展开科学分析与知识发现。当前,电子踪迹、社交媒体、数字文本与空间位置信息是4种最具代表性的社会科学大数据类型,它们已被广泛应用于诸多社会研究领域之中,在推动数据分析方法创新的同时,也极大地拓展了社会科学的研究视野。尽管仍面临着数据、技术、知识边界和社会伦理等方面的种种限制,社会科学大数据计算的发展潜力无疑是巨大的。

The accumulation of data and the progress of technologies in the big data era have laid a new opportunity for the development of Computational Social Science. Based on the latest computer technology, big data computing, which has replaced social simulation as the core issue of computational social science, aims to mine ＂knowledge-data＂ from big data which can meet the needs of social research, and then to draw academic conclusions by the scientific analysis of knowledge-data. Digital traces, social media, digital text and GPS are four typical types of social science big data currently, and have been widely used in many areas of social research. These data not only promote the innovation of research methods, but also greatly expand the research field of social science. Despite many limitations and boundaries, such as data representativeness, authenticity, validity, and ethics, the development potential of big data computing in social science is undoubtedly enormous.