摘要： 近年来，数据驱动的计算社会科学发展迅速，而各科研主体对数据资源的占有与处理能力存在差异，由此产生知识生产的不平等问题，即谁能从事计算社会科学研究？在拉图尔“计算中心”概念基础上，可以构建数据形态的分析框架，即将数据视为要素、资本与符号，对应计算社会科学知识生产过程的进入、竞逐与垄断阶段。在进入阶段，数据作为生产要素成为科研门槛，基础设施与数字技能构成进入壁垒；在竞逐阶段，数据要素转化为数据资本，不同主体围绕数据展开合作与应用，导致资源与权力逐渐向中心集聚；在垄断阶段，数据资本经由传播与奖励体系符号化，转化为话语权与评价权，进一步固化知识生产中的等级结构。即便如此，未来的计算社会科学仍有可能迈向共建与共享的多元主体格局。

关键词: 计算社会科学, 数据要素, 数据资本, 数据符号, 计算中心

Abstract: Computational social science (CSS), driven by data, has developed rapidly. However, disparities in the possession and processing capabilities of data resources among various research entities have led to inequalities in knowledge production, raising the critical question: Who can engage in computational social science research? Building on Latour’s concept of “centres of calculation”, it constructs an analytical framework for data forms, viewing data as an element, capital, and symbol, which correspond to the entry, competition, and monopoly stages in the CSS knowledge production process. At the entry stage, data as a productive factor becomes a research threshold, with infrastructure and digital skills constituting barriers to entry. During the competition stage, data elements are transformed into data capital, as different entities collaborate and apply data, leading to a gradual concentration of resources and power towards the center. In the monopoly stage, data capital is symbolized through dissemination and reward systems, converting into discourse power and evaluation power, further solidifying the hierarchical structure in knowledge production. Despite this, the future of computational social science still holds the potential to move towards a pluralistic landscape of co-construction and shared participation among multiple entities.

Key words: computational social science, data element, data capital, data symbol, centres of calculation