Social Identity in Online Microfinance and Public Goods Provision

在线小额信贷和公共产品供应中的社会认同

• 批准号: 1111019
• 负责人: Yan Chen
• 金额: $ 50万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1111019&HistoricalAwards=false
• 关键词: Social; Identity; Online; Microfinance; Public

This project represents an interdisciplinary research effort to investigate the effects of social identity on lender behavior in an online microfinance community (kiva.org) and the selection of social identities. Social identity research in economics predicts that a salient group identity and group competition increases individual contribution to public goods.The researchers will apply social identity and social preference theory to analyze the Kiva lending data at the individual and team level. Results from the analysis will yield insights to one of the most important yet unresolved problems in social identity research, the selection of identity and the formation of norms within a social group. This work represents the first attempt to bridge text and network data mining techniques with social identity theory. Novel text mining and machine learning models will be developed that advance the state-of-the-art of mining of online communities.More than one billion people globally live in absolute poverty, most also excluded from the formal banking sector. To alleviate poverty, microfinance programs emerge in many parts of the world to provide small loans to the poor. Currently about 10 million households are served by microfinance programs. This research investigates incentives to increase lender participation and lending activities on Kiva. Preliminary analysis indicates that the lending teams program is effective in increasing loan activities. Results from the analysis will benefit Kiva and other microfinance programs. Increased participation and lending activities will help realize the World Bank's goal of serving 100 million poor households.

本项目代表了一个跨学科的研究努力，以调查社会身份对贷款人的行为在一个在线小额信贷社区（kiva.org）和社会身份的选择的影响。经济学中的社会认同研究预测，显著的群体认同和群体竞争会增加个人对公共产品的贡献。研究人员将运用社会认同和社会偏好理论，从个人和团队层面分析Kiva贷款数据。从分析的结果将产生洞察社会身份研究中最重要的尚未解决的问题之一，身份的选择和规范的形成在一个社会群体。这项工作是第一次尝试桥梁文本和网络数据挖掘技术与社会身份理论。将开发新颖的文本挖掘和机器学习模型，以推进在线社区挖掘的最新发展。全球有超过10亿人生活在绝对贫困中，其中大多数人还被排除在正规银行部门之外。为了减轻贫困，世界许多地方出现了小额信贷计划，向穷人提供小额贷款。目前，约有1 000万个家庭得到小额信贷方案的服务。本研究调查激励措施，以增加贷款人的参与和贷款活动的Kiva。初步分析表明，贷款小组方案在增加贷款活动方面是有效的。分析结果将有利于Kiva和其他小额信贷计划。增加参与和贷款活动将有助于实现世界银行为1亿贫困家庭提供服务的目标。