The wonders of the Zooniverse: Modelling and optimising volunteer participation in online citizen science

数字经济的增长极大地影响了人们相互交流和参与许多活动的方式。虽然以前已经对这种转变的商业和社会方面进行了一些深入的探讨，但是第三部门和志愿活动还没有受到经济和管理科学同样程度的分析。这一提议将填补数字经济中对志愿服务实践的理解和建模方面的重大空白。这个研究项目特别关注的是被称为Zooniverse的网站群，这是一个非常成功的在线公民科学和众包项目群，如Galaxy Zoo和Cell Slider。这些网站的志愿者贡献他们的时间对科学数据进行分类，从遥远星系的图像到天气模式和癌细胞。该项目将根据直接从Zooniverse志愿者那里获得的数据，包括态度、行为和对激励措施的反应，重新评估现有的志愿服务经济模式。这项研究将允许发展新的志愿服务和众包经济模式，这将为参与和参与在线志愿服务和公民科学计划提供更有效的解释。该项目还将研究如何通过优化与参与者的一系列具体和量身定制的直接互动来提高和维持志愿服务水平。研究结果将用于改进和开发公民科学项目的管理和组织的新模型，以促进科学进步和社会价值的创造。

The growth in the digital economy has dramatically affected the way in which people interact with each other and engage with a number of activities. Although the commercial and social aspects of this transition have previously been explored in some depth, third-sector and volunteering activity has not been subjected to the same degree of analysis from the economic and management sciences. This proposal will fill a significant gap in the understanding and modelling of volunteering practices in the digital economy.The particular focus of this research project is the group of websites known as the Zooniverse, a highly successful grouping of online citizen science and crowdsourcing projects such as Galaxy Zoo and Cell Slider. Volunteers to these sites donate their time to classifying data of scientific interest, ranging from images of distant galaxies to weather patterns and cancer cells. This project will re-evaluate existing economic models of volunteering in light of data obtained directly from Zooniverse volunteers, including attitudes, behaviours and responses to incentives. The research will allow for the development of new economic models of volunteering and crowdsourcing that will offer more effective explanations for participation and engagement with online volunteering and citizen science initiatives. The project will also investigate ways in which volunteering levels can be increased and sustained through the optimisation a specific and tailored series of direct interactions with participants. The results will be used to refine develop new models for the management and organisation of citizen science initiatives in order to enhance the creation of scientific progress and social value.