数据革命与人口研究新视野  

Digital Data Revolution and the New Horizons of Population Studies

作　　者：殷佳 梁玉成[1] YIN Jia;LIANG Yu-cheng(School of Sociology&Anthropology,Sun Yat-sen University,Guangzhou 510275)

机构地区：[1]中山大学社会学与人类学学院,广东广州510275

出　　处：《南方人口》2024年第1期1-17,共17页South China Population

摘　　要：数字时代,互联网的传播和人工智能技术的快速发展改变了数据的生产和使用方式,促进了可用数据的爆炸式增长,在社会科学领域掀起了一场数据革命,迎来了从设计数据(过去)到痕迹数据(现在)再到生成性数据(未来)的发展变迁。痕迹数据包括电子存档数据、设备感知数据和网络平台数据,相较传统的设计数据在时效、规模、范围和成本上的优势为人口研究的拓展和创新带来了巨大潜力。在研究内容上,痕迹数据通过强化流动性测量、收集人口行为背景、捕捉特定研究对象,极大地推动了人口的迁移流动研究,并为微观的人口过程分析提供了丰富洞见。在研究思路上,痕迹数据从时间尺度改变了人口动态的分析单位,空间维度打破了传统人地分离的研究瓶颈,方法上要求促进不同来源类型数据的结合提升研究效度,应用中推进了人口与社会动态的实时监测与预警,为循证决策提供了及时有效的研究支撑。新时代,对痕迹数据的挖掘需要充分发挥数据想象力,加快对前沿计算方法的掌握和跨学科合作的形成,建立现代化的数据生态系统以实现数据的开放、共享和使用。The digital era,driven by the advancements in internet communication and artificial intelligence,has revolutionized the production study and its usage of data,which is resulting in an explosion of available data and reshaping social sciences through the data revolution,marking a transition from designed data(the past)to trace data(the present)and further onto generative data(the future).Tracing data,encompassing the data from electronic archives,device-sensed,and network platform,offer great advantages over traditional design data in terms of timeliness,scale,scope,and cost,and thus unlocks substantial potentialities for innovation in population studies.Tracing data can significantly advances the study of population migration dynamics,providing rich insights for micro-level demographic analyses by enhancing the mobility measurements,collecting the background information of demographic behaviors,and capturing the targeted subject.Methodologically,tracing data changes the analysis units of population dynamics by altering the time scale,breaks the bottleneck of living place separating from the registered place by the digital dynamic data of spatial dimensions,and brings about the integration of diverse data sources to enhance research validity.In practical terms,tracing data facilitates real-time monitoring and early warning of population and social dynamics and provides timely and effective research support for evidence-based decision-making.This new era of digital data requires more efforts to explore the great potentiality of tracing data application in population studies by leveraging the data imagination,applying the cutting-edge computational methods,fostering inter-disciplinary collaboration,and establishing a modernized data ecosystem for the open,shared,and effective data utilizatio.

关 键 词：痕迹数据 人口研究 计算社会科学 生成性数据 

分 类 号：C92-05[社会学—人口学]