Collaborative Research: Experiments with Real World Social Networks

合作研究：现实世界社交网络的实验

• 批准号: 0527795
• 负责人: Tanya Rosenblat
• 金额: $ 26.66万
• 依托单位: Wesleyan University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0527795&HistoricalAwards=false
• 关键词: Collaborative; Research; Experiments; Real; World

Social networks allow us to both learn about the world and learn about others. Networks can therefore promote technological progress and consumer choice on the one hand, and are sources of trust in communities on the other hand. Our goal is to decompose the channels through which both of these phenomena operate. The PIs conduct two large field experiments with about 2,500 students at Harvard University. In the first study, they will provide samples of new and complex products such as PDA's to a randomly selected group of students. They will use various treatments including print and online advertising to obtain valid instruments for estimating interaction channels. By measuring both initial and final valuations as well as subjects' knowledge about the functionality of each product the research design can separate social learning, whether it be learning from information (strong social learning) or learning from observing friends' valuations (weak social learning), from social influence which changes preferences directly. In the second learning project the PIs will generate private signals about the quality of four imaginary companies and then observe how subjects aggregate this information in the social network. By using the same subject pool we can further refine our model of social learning.The last part of this project is a study of trust that will use field experiment techniques in Peru. We measure trust through a new microfinance program where borrowers can obtain low-interest rate loans by finding a sponsor from a predetermined set group of people in the community who are willing to cosign the loan. This research will help us to better understand how people learn from the experiences of others. The research design will allow the PIs to break this kind of "social learning" into two different pieces by measuring both outcomes and information transmission. A better understanding of the channels of social learning can help policy makers design more effective interventions such as encouraging contributions to retirement savings plans.

社交网络让我们既能了解世界，又能了解他人。 因此，网络一方面可以促进技术进步和消费者选择，另一方面也是社区信任的来源。我们的目标是分解这两种现象运作的渠道。 PI在哈佛大学进行了两次大型实地实验，约有2,500名学生参加。在第一项研究中，他们将向随机选择的一组学生提供新的和复杂的产品样品，如PDA。他们将使用各种治疗方法，包括印刷和在线广告，以获得有效的工具，估计互动渠道。通过测量初始和最终的评价以及受试者对每个产品功能的了解，研究设计可以将社会学习（无论是从信息中学习（强社会学习）还是从观察朋友的评价中学习（弱社会学习））与直接改变偏好的社会影响分开。在第二个学习项目中，PI将生成关于四家虚构公司质量的私人信号，然后观察受试者如何在社交网络中聚合这些信息。通过使用相同的主题库，我们可以进一步完善我们的社会学习模型。这个项目的最后一部分是信任的研究，将使用现场实验技术在秘鲁。我们通过一个新的小额信贷项目来衡量信任度。在这个项目中，借款人可以从社区中预先确定的一组愿意共同签署贷款的人中找到一个担保人，从而获得低息贷款。这项研究将帮助我们更好地了解人们如何从他人的经验中学习。 研究设计将允许PI通过测量结果和信息传输将这种“社会学习”分为两个不同的部分。更好地了解社会学习的渠道可以帮助政策制定者设计更有效的干预措施，例如鼓励为退休储蓄计划捐款。