Collaborative Research: Social Diffusion in Online Media for Reaching Hidden Communities and Underrepresented Groups

合作研究：网络媒体的社会扩散，覆盖隐藏社区和代表性不足的群体

• 批准号: 1111016
• 负责人: Christopher Homan
• 金额: $ 20.72万
• 依托单位: Rochester Institute of Tech
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1111016&HistoricalAwards=false
• 关键词: Collaborative; Research; Social; Diffusion; Online

The goal of this project is to use peer-driven recruitment to sample from and send information to hidden, underrepresented, or underground online communities. Specifically, the project will examine how social media can be used to extract information from and distribute information to hidden communities, determine whether the framework to be developed can provide new insights into the behavior of community members, advance the science of peer-to-peer sampling techniques, and determine whether trust in social media affects the peer-to-peer recruitment process.Intellectual MeritThis project will serve to answer the following questions. How can we best apply computational resources that are associated with online social media to improve processes for collecting information from and distributing information to hidden populations? To what degree do the known deficiencies in state-of-the-art bias estimators impact the effectiveness of peer-to-peer-based sampling and how well can these deficiencies be corrected by new estimators and/or sampling design? To what extent do individuals invest trust in various social media (particularly Facebook and email) and how much does degree-of-trust affect peer-to-peer recruitment processes, especially with respect to identification with a hidden or marginalized group? These are important questions, and answers to them will serve to advance the both the social and computational sciences, and their synergistic combinations. Broader ImpactsThis project will provide an open source system for remotely interacting with online communities, particularly but not limited to hidden communities. The project will have a substantial education component in that the proposed system will have a simulation mode that will enable it to be used for class projects. By providing a way to address problems that impact underrepresented groups, it will also provide meaningful research and educational opportunities in computing to members of those groups. In addition, it will establish an interdisciplinary, intercollegiate laboratory in online social network research that will institutionalize preexisting working relationships and provide a home for an ongoing seminar series in network science.

该项目的目标是使用同行驱动的招聘来从隐藏的、代表性不足的或地下的在线社区中抽样并发送信息。具体来说，该项目将研究如何使用社交媒体从隐藏社区中提取信息并向隐藏社区分发信息，确定要开发的框架是否可以提供对社区成员行为的新见解，推进点对点抽样技术的科学，并确定对社交媒体的信任是否会影响同侪招募过程。智力优点这个项目将回答以下问题。我们如何最好地应用与在线社交媒体相关的计算资源，以改善从隐藏人群收集信息和向隐藏人群分发信息的过程？在何种程度上，已知的缺陷，在国家的最先进的偏差估计影响的有效性，对等的抽样，以及如何可以纠正这些缺陷，新的估计和/或抽样设计？ 个人在多大程度上信任各种社交媒体（特别是Facebook和电子邮件），信任度在多大程度上影响点对点招聘过程，特别是在认同隐藏或边缘化群体方面？这些都是重要的问题，对它们的回答将有助于推进社会科学和计算科学，以及它们的协同组合。更广泛的影响这个项目将提供一个开源系统，用于与在线社区进行远程交互，特别是但不限于隐藏社区。该项目将有一个实质性的教育组成部分，因为拟议的系统将有一个模拟模式，使其能够用于课堂项目。通过提供一种方法来解决影响代表性不足的群体的问题，它还将为这些群体的成员提供有意义的计算研究和教育机会。此外，它还将建立一个在线社会网络研究的跨学科、跨学院实验室，使先前存在的工作关系制度化，并为正在进行的网络科学系列研讨会提供一个场所。