课题基金 / 基金详情

HCC: Small: Experiments in Community Q&A

HCC: Small: Experiments in Community Q&A
HCC:小型:社区 Q 中的实验
批准号:
1319382
负责人:
Joseph Konstan
金额:
$50.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2018-08-31

项目摘要

项目成果

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中文摘要
翻译
在线社区问答系统,如Yahoo!答案提供了一个场所,人们可以提出问题,提供答案,浏览和评论两者。这样的站点现在是许多站点在线交互的中心部分,包括用于软件开发、税务准备和产品支持的专门站点。在这个项目中,pi将实验性地回答一系列因果问题,这些问题是从不同的研究文献中得出的,关于如何提高Q& a系统的性能,特别是什么导致人们提供高质量的答案(和问题),如何安排问题以便由最好的成员回答,推荐和简介如何影响问题和答案,以及不同类型的激励在多大程度上影响网站上的行为。这项研究之所以重要,是因为在线问答系统已经成为个人和企业获取信息和建议的重要来源,是企业帮助客户相互支持的重要而经济的方式,也是网络搜索引擎的重要内容来源。通过理解这些系统,构建使用模型并测试设计以支持其改进的操作,该项目将帮助系统设计者理解可以为用户促进有益的社会体验的方法,并且可以告知有价值的社区贡献知识库的构建。其他好处包括为其他研究人员发布数据集和培训学生研究人员。
英文摘要
Online community question-and-answer systems such as Yahoo! Answers provide a venue where people can pose questions, provide answers and browse and comment on both. Such sites are now a central part of online interaction on a wide range of sites, including specialized sites for software development, tax preparation, and product support. In this projects, the PIs will experimentally answer a set of causal questions drawn from diverse research literatures about how to improve the performance of Q&A systems, specifically what leads people to provide good quality answers (and questions), how to route questions so they are answered by the best possible member, how referrals and profiles affect questions and answers, and to what extent different kinds of incentives affect behavior on the site.The proposed research is important because online question and answer systems have become an important source of information and advice for individuals and businesses, an important and economical way for businesses to help their customers support each other, as well as an important source of content for web search engines. By understanding these systems, building models of usage and testing designs to support their improved operation, the project will help systems designers understand approaches that can promote beneficial social experiences for users and that can inform the construction of valuable community-contributed repositories of knowledge. Additional benefits include the release of data sets for other researchers and the training of student researchers.
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Collaborative Research: CCRI: New: A Research News Recommender Infrastructure with Live Users for Algorithm and Interface Experimentation
  • 批准号:
    2232551
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