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英文标题: | Social Prediction:A New Research Paradigm Based on Machine Learning |
摘要: | 社会学是对社会行动提供诠释和反事实因果解释的科学。社会学定量研究的因果性解释,必须能够作为预测社会现象的基础。受到数据和算力限制,多年来社会学定量研究的主要取径是通过统计检验实现关联和因果分析,而无力进行预测。本文对“社会预测”这一概念的历史脉络进行梳理,阐述了通过机器学习方法实现社会预测的科学原理和当代路径,并对社会预测进行了再定义。在此基础上,本文进一步探讨了社会预测的学术价值、治理价值和话语价值,并阐述了其作为定量社会研究前沿的范式突破意义。我们认为,利用机器学习实现社会预测,是中国社会学特别是计算社会学引领国际前沿的重要契机,对于加快构建中国特色哲学社会科学具有重要意义。 |
英文摘要: | Sociology is a science concerning itself with interpretive understanding of social action as well as causal explanation. A causal explanation should be the foundation of prediction. For many years, constrained by data and computing power, quantitative research of social science has primarily focused on statistical test to analyze correlation and causality, leaving predictions largely ignored. By sorting out the historical context of “social prediction”, this paper redefines this concept by introducing why and how machine learning can help prediction in a scientific way. This paper further summarizes the academic value and governance value of social prediction, and suggests that it be a potential breakthrough in contemporary social research paradigm. We believe, through machine learning, we can witness the advent of an era of paradigm shift from correlation, causality to social prediction, providing a rare opportunity for sociology in China to lead the international frontier of computational social sciences, and accelerating the construction of philosophy and social science with Chinese characteristics. |
作者: | 陈云松、吴晓刚、胡安宁、贺光烨、句国栋 |
作者单位: | 南京大学-约翰斯·霍普金斯大学中美文化研究中心、南京大学社会学院(陈云松);香港科技大学应用社会经济研究中心(吴晓刚);复旦大学社会学系(胡安宁);南京大学社会学院(贺光烨、句国栋) |
期刊: | 社会学研究 |
年.期:页码 | 2020.3: |
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关键词: | 社会预测;机器学习;研究范式;定量研究方法;计算社会学 |
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项目基金: | 本研究获得国家社会科学基金重大项目“大数据驱动的网络社会心态发展规律与引导策略研究”(19ZDA149)支持。 |
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