The substantial volume, continued growth, and resulting complexity of the scientific literature not only increases the need for systematic, replicable, and rigorous literature reviews, but also highlights the natural limits of human researchers’ information processing capabilities. In search of a solution to this dilemma, computational techniques are beginning to support human researchers in synthesizing large bodies of literature. However, actionable methodological guidance on how to design, conduct, and document such computationally augmented literature reviews is lacking to date. We respond by introducing and defining computational literature reviews (CLRs) as a new review method and put forward a six-step roadmap, covering the CLR process from identifying the review objectives to selecting algorithms and reporting findings. We make the CLR method accessible to novice and expert users alike by identifying critical design decisions and typical challenges for each step and provide practical guidelines for tailoring the CLR method to four conceptual review goals. As such, we present CLRs as a literature review method where the choice, design, and implementation of a CLR are guided by specific review objectives, methodological capabilities, and resource constraints of the human researcher.

科学文献的数量巨大，持续增长以及随之而来的复杂性，不仅增加了对系统，可复制和严格的文献综述的需求，而且突显了人类研究人员信息处理能力的天然局限性。为了解决这一难题，计算技术开始支持人类研究人员合成大量文献。但是，迄今为止，尚缺乏有关如何设计，进行和记录这种计算能力增强的文献综述的可行的方法学指导。我们通过引入和定义计算文献评论来做出回应（CLR）作为一种新的审查方法，并提出了六步路线图，涵盖了从确定审查目标到选择算法和报告调查结果的CLR流程。通过确定关键的设计决策和每个步骤的典型挑战，我们使CLR方法可供新手和专家用户使用，并为将CLR方法调整为四个概念性审查目标提供实用指南。因此，我们将CLR作为一种文献综述方法进行介绍，其中CLR的选择，设计和实施受特定研究目标，方法论能力和人类研究人员的资源限制的指导。