HCC-Large: Collaborative Research: Understanding Online Volunteer Communities: Toward Theory-Based Design

该项目将开发在线志愿者社区(OLVC)的面向设计的科学，如维基百科、SourceForge和TripAdvisor。这些网站吸引了数十万人--不是为了玩游戏或社交--而是为了制作内容。OLVCs制作的内容很有价值。维基百科是网络上最受欢迎的十大网站之一。SourceForge是开源软件运动的中心，数以千计的项目使用它来组织他们的工作。TripAdvisor将旅行者聚集在一起，他们的评论相互帮助，寻找和审查酒店和服务。尽管取得了这些成功，但OLVC仍面临着真正的挑战。大多数公司很快就会失败，即使是最成功的公司也有问题。超过三分之二的SourceForge项目很快就不活动了。就连维基百科也在苦苦挣扎：破坏是一个持续存在的问题，三分之二的文章是存根--质量最差的文章太短，无法提供百科全书式的报道--最近的数据表明，维基百科的持续增长可能已经停止，甚至逆转。以设计为导向的OLVCs科学可以帮助解决这些问题。将开展四项具体的研究活动，以产生这门科学。首先，该项目将从以前的研究中挖掘结果，以创建模型、制定假设并定义关键的成功指标。其次，它将开发算法和接口，以帮助OLVCs更好地发挥作用。第三，它将评估真实的OLVC中的机制，例如，通过实验衡量不同的社会比较界面在多大程度上激励志愿者加强他们的活动。最后，该项目将提炼结果，为在线志愿者社区制定可推广的设计原则。该项目将开发一套广泛的软件机制，以解决在线志愿者社区的重要和一般问题。算法和接口将在真实的OLVC中进行系统评估，从而提供关于其有效性的经验性知识体系。此外，该项目的成果还可以反馈给最初为线下志愿服务开发的先进社会科学理论。

This project will develop a design-oriented science of online volunteer communities (OLVCs) such as Wikipedia, SourceForge, and TripAdvisor. These web sites attract hundreds of thousands of people - not to play games or socialize - but to produce content. The content produced by OLVCs is valuable. Wikipedia is among the ten most popular sites on the Web. SourceForge is the hub of the open source software movement, used by thousands of projects to organize their work. TripAdvisor brings together travelers whose reviews help each other find and vet hotels and services. Despite these successes, OLVCs face real challenges. Most fail quickly, and even the most successful have problems. Over two-thirds of SourceForge projects become inactive fairly quickly. Even Wikipedia struggles: vandalism is a constant problem, two thirds of the articles are stubs - the lowest quality article, which are too short to provide encyclopedic coverage - and recent data suggests that Wikipedia's constant growth may have halted and even reversed. A design-oriented science of OLVCs could help solve these problems. Four specific research activities will be carried out to produce this science. First, the project will mine results from prior research to create models, formulate hypotheses, and define key success metrics. Second, it will develop algorithms and interfaces to help OLVCs function better. Third, it will evaluate the mechanisms in real OLVCs, for example, with experiments that measure the extent to which different social comparison interfaces motivate volunteers to step up their activity. Finally, the project will abstract the results to develop generalizable design principles for online volunteer communities. This project will develop a broad set of software mechanisms to solve important and general problems of online volunteer communities. The algorithms and interfaces will be evaluated systematically in real OLVCs, thus providing an empirically grounded body of knowledge about their effectiveness. In addition, the results of this project can feed back to advance social science theories originally developed for offline volunteering.