As the crowdsourcing approach is increasingly being used for digitizing cultural heritage artifacts, there is a rising need for volunteer engagement in such collaborative digital humanities projects. This study focuses on the less explored topic of imbalanced volunteer engagement (IVE); it refers to the fact that most volunteers tend to focus only on a small portion of tasks, making it challenging to sustain cultural heritage crowdsourcing (CHC) projects. Using a public dataset containing 145,168,535 items captured from the Australian Newspaper Digitisation Project, we utilized a machine learning-based causal inference approach to investigate the IVE problem by examining the causal relationships between task content characteristics and volunteer engagements. We used the directed acyclic graph (DAG) to represent the structure, such that a causal relationship consisting of 11 nodes and 16 edges was obtained. Specifically, four causes, including task category, word count, number of task lists, and whether the task was illustrated, directly affect IVE. We further discuss these findings from a theoretical perspective and suggest three propositions: a) nudge-like intervention of a task list, b) subjective (perceived) low task complexity, and c) attraction of task presentation, alleviating the IVE problem. This study contributes to the literature on volunteer engagement in the CHC context and sheds new light on the design and implementation of collaborative digital humanities projects.

随着众包方法越来越多地被用于将文化遗产文物数字化，越来越需要志愿者参与此类协作数字人文项目。本研究侧重于较少探索的不平衡志愿者参与主题（IVE）；它指的是大多数志愿者往往只专注于一小部分任务，这使得维持文化遗产众包 (CHC) 项目具有挑战性。使用包含从澳大利亚报纸数字化项目中捕获的 145,168,535 个项目的公共数据集，我们利用基于机器学习的因果推理方法通过检查任务内容特征和志愿者参与之间的因果关系来调查 IVE 问题。我们使用有向无环图（DAG）来表示结构，这样就得到了由11个节点和16条边组成的因果关系。具体来说，任务类别、字数、任务列表数量、任务是否有插图四个原因直接影响IVE。我们从理论的角度进一步讨论了这些发现，并提出了三个命题：a）任务列表的轻推式干预，b）主观（感知）低任务复杂性，以及 c）任务呈现的吸引力，缓解 IVE 问题。本研究为 CHC 环境中志愿者参与的文献提供了帮助，并为协作数字人文项目的设计和实施提供了新的思路。直接影响IVE。我们从理论的角度进一步讨论了这些发现，并提出了三个命题：a）任务列表的轻推式干预，b）主观（感知）低任务复杂性，以及 c）任务呈现的吸引力，缓解 IVE 问题。本研究为 CHC 环境中志愿者参与的文献提供了帮助，并为协作数字人文项目的设计和实施提供了新的思路。直接影响IVE。我们从理论的角度进一步讨论了这些发现，并提出了三个命题：a）任务列表的轻推式干预，b）主观（感知）低任务复杂性，以及 c）任务呈现的吸引力，缓解 IVE 问题。本研究为 CHC 环境中志愿者参与的文献提供了帮助，并为协作数字人文项目的设计和实施提供了新的思路。