CAREER: Mental Models and Critical Mass: Shaping the Success of Online Communities

职业：心理模型和临界质量：塑造在线社区的成功

• 批准号: 1350253
• 负责人: Richard Wash
• 金额: $ 48.97万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-15 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1350253&HistoricalAwards=false
• 关键词: CAREER; Mental; Models; Critical; Mass

As new computing and communication technologies become mainstream, online communities are transforming journalism and other industries to support more interactive, community-driven work. This project will study how mental models of online communities are formed, how they shape expectations about the future of the community, how they co-evolve with the community over time, and how they aggregate to form a critical mass that is essential for successful work and community survival. In many such online communities, participation is voluntary: each person must look at the community, develop a mental model of what that community is, how it works, and what it means for them to join, and then make a decision about whether they want to participate. And then, as the community evolves and changes, they need to continually decide whether and how to participate.This research will triangulate three research methods to understand how individuals form mental models of online communities, and how mental models of multiple individuals interact and aggregate to form a larger community. First, it will use qualitative interviews to understand how individuals make sense of a new online community and how they make continuing participation decisions in communities they are already part of. Second, it will use a series of human subjects lab experiments to characterize how people form mental models of both the content available in an online community, and the other users of an online community. These experiments will also help to understand how a user's mental model helps her interpret the community's reactions to her participation. Finally, this project will use statistical analysis and formal mathematical modeling of existing online communities to understand how online communities grow over time and when people choose to leave online communities. Results of this research will be of general value in designing, managing, and participating in many kinds of online communities, as well as contributing to education in the information, cognitive, and social sciences. A unique, cross-disciplinary education program will be created that trains students to use this research to build special-purpose online communities. This program will include a joint class linking a School of Journalism with a department of Telecommunication, Information Studies and Media. This class will form cross-disciplinary teams who spend the semester creating and growing an online community. This partnership will teach students to apply social science and computer science research for real-world applications, and work on collaborative, cross-disciplinary teams that include technical people, creative people, and topic experts. It represents a new type of education in journalism that will bring students into new, community-driven methods of doing journalism, based more on curating content and facilitating discussion than on original, unidirectional reporting.

随着新的计算和通信技术成为主流，在线社区正在改变新闻业和其他行业，以支持更具互动性、社区驱动型的工作。这个项目将研究在线社区的心理模型是如何形成的，它们如何塑造对社区未来的期望，它们如何随着时间的推移与社区共同进化，以及它们如何聚集成对成功的工作和社区生存至关重要的临界量。在许多这样的在线社区中，参与是自愿的：每个人都必须审视这个社区，建立一个心理模型，了解这个社区是什么，它是如何运作的，以及加入对他们意味着什么，然后决定是否想要参与。然后，随着社区的演变和变化，他们需要不断地决定是否以及如何参与。本研究将通过三角测量三种研究方法来理解个体如何形成在线社区的心理模型，以及多个个体的心理模型如何交互和聚合形成一个更大的社区。首先，它将使用定性访谈来了解个人如何理解一个新的在线社区，以及他们如何在他们已经成为社区一部分的社区中做出继续参与的决定。其次，它将使用一系列人类受试者实验室实验来表征人们如何形成在线社区中可用内容和在线社区其他用户的心理模型。这些实验还将有助于理解用户的心理模型如何帮助她解释社区对她的参与的反应。最后，这个项目将使用现有在线社区的统计分析和正式数学建模来了解在线社区是如何随着时间的推移而增长的，以及人们何时选择离开在线社区。本研究的成果将对设计、管理和参与多种类型的在线社区具有普遍的价值，并对信息、认知和社会科学的教育做出贡献。将创建一个独特的、跨学科的教育计划，培训学生利用这项研究建立特殊目的的在线社区。该计划将包括一个联合课程，将新闻学院与电信、信息研究和媒体系联系起来。这门课将组成跨学科的团队，他们将用整个学期的时间创建和发展一个在线社区。这一合作伙伴关系将教会学生将社会科学和计算机科学研究应用于现实世界的应用，并在包括技术人员、创意人员和主题专家在内的协作、跨学科团队中工作。它代表着一种新型的新闻教育，它将把学生带入社区驱动的新闻工作新方法，更多地基于策划内容和促进讨论，而不是原创的、单向的报道。