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.

该项目代表了一项跨学科研究工作，旨在调查社会身份对在线小额信贷社区 (kiva.org) 中贷款人行为的影响以及社会身份的选择。经济学中的社会认同研究预测，显着的群体认同和群体竞争会增加个人对公共物品的贡献。研究人员将应用社会认同和社会偏好理论来分析个人和团队层面的Kiva借贷数据。分析结果将为社会身份研究中最重要但尚未解决的问题之一、社会群体内身份的选择和规范的形成提供见解。这项工作代表了将文本和网络数据挖掘技术与社会身份理论联系起来的首次尝试。我们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先进水平。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业之外。为了减轻贫困，世界许多地方都出现了小额信贷计划，向穷人提供小额贷款。目前，约有 1000 万家庭接受小额信贷计划的服务。本研究调查了增加贷款人参与 Kiva 和贷款活动的激励措施。初步分析表明，贷款团队计划对于增加贷款活动是有效的。分析结果将使 Kiva 和其他小额信贷项目受益。增加参与和贷款活动将有助于实现世界银行服务一亿贫困家庭的目标。