从计量史学迈向基于大数据计算思维的新历史学--对当代西方史学量化研究新发展的思考  

From Quantitative Historiography to A New Historiography of Big Data and Computational Thinking: Reflections on the New Tendency of Quantitative Historical Research in the West

作　　者：韩炯[1] 

机构地区：[1]上海财经大学人文学院讲师,200043

出　　处：《史学理论研究》2016年第1期65-74,159,共10页Historiography Bimonthly

基　　金：国家社科基金重大项目“当代国际史学研究及其发展趋势”(项目编号:12&ZD186)阶段性成果

摘　　要：进入信息时代,历史学能否彻底走出20世纪下半叶诸多批评中指出的"量化陷阱",而真正成为"基于大数据计算"且定量与定性很好结合的历史科学,是当今历史研究领域须加深入思索的新问题。量化研究应用于历史学的合理性和重要性首先在于它有助于历史学家更好地解决"质"的问题进而推动历史学成为真正的历史科学。论文通过回顾西方史学量化研究在20世纪经历的两个不同演进阶段及其基本特征,分析指出,系列史/序列史和美国新经济史学的研究实践表明,量化研究对于历史学寻求科学化目标实现的重要价值正越发凸显。伴随信息革命的到来,借助于大数据时代的优势,量化研究方法可能引发历史学的深层革命性变革。论文包括三个部分:量化研究是历史学科学性的重要保证、西方史学中的量化研究演进轨迹和新趋势、当代西方史学量化研究新发展的思考。倘若克服对大数据的曲解并调整历史研究思维方法,量化历史研究将带来历史学领域革命性变革。量化历史研究未来将大有前途。Since the information revolution,the main question confronting today's historians is whether historical writing can transcend 'the trap of definite quantitative determination'and become a historical science,using Big Data and computational thinking. Quantitative research has helped historians to locate hard proof,making historical study more a science. Examples of which are the practices of histoire serielle and Cliometrics( the new economic historiography). Meanwhile,there is also the need to combine quantitative and qualitative methods. The author contends that this combination would lead to a new historiography of Big Data and computational thinking. His article consists of three parts: 1) How quantitative research helps ensure the scientificity of historical study; 2) The development of quantitative method in Euro American historiography; and 3) Reflections on the application of quantitative method in historical writing as seen today. He concludes that if used properly,the quantitative research using Big Data and computational thinking can revolutionize the study of history in the near future.

关 键 词：史学理论 历史计算思维 计量史学 大数据 

分 类 号：K091[历史地理—历史学]