首页> 外文期刊>Information Processing & Management >Quality assessment of answers with user-identified criteria and data-driven features in social Q&A
【24h】

Quality assessment of answers with user-identified criteria and data-driven features in social Q&A

机译:社交问答中具有用户识别标准和数据驱动功能的答案的质量评估

获取原文
获取原文并翻译 | 示例
       

摘要

The purpose of the current study is to identify the user criteria and data-driven features, both textual and non-textual, for assessing the quality of answers posted on social questioning and answering sites (social Q&A) across four different knowledge domains—Science, Technology, Art and Recreation. A comprehensive review of literature on quality assessment of information produced in social contexts was carried out to develop the theoretical framework for the current study. A total of 23 user criteria and 24 data features were proposed and tested with high-quality answers obtained from four social Q&A sites in Stack Exchange. Findings indicate that content-related criteria and user and review features were the most frequently used in quality assessments, while the importance of user criteria and data features was variable across the knowledge domains. In the Technology Q&A site containing mostly self-help questions, the utility class was the most frequently used group of criteria. The popularity of the socio-emotional class was more apparent in discussion-oriented topic categories such as Art and Recreation, where people seek others’ opinions or advice. Users of Art and Recreation Q&A sites in Stack Exchange appear to place more value on answerers’ efforts and time, good attitudes or manners, personal experience, and the same taste. The importance of user features and the emphasis on answerer's expertise on the Science Q&A site was observed. Examining the connection or gap between user quality criteria and data features across the knowledge domains could help to better understand users’ evaluation behaviors for their preferred answers, and identify the potential of social Q&A for user education/intervention in answer quality evaluation. This examination also offers practical guidance for designing more effective social Q&A platforms, considering how to customize community support systems, motivate contributions, and control content quality.
机译:本研究的目的是识别文本和非文本的用户标准和数据驱动功能,以评估在四个不同知识领域(科学,技术,艺术与娱乐。对在社会背景下产生的信息的质量评估进行了文献综述,以发展本研究的理论框架。总共提出了23个用户标准和24个数据功能,并通过从Stack Exchange中四个社交问答站点获得的高质量答案进行了测试。研究结果表明,与内容相关的标准以及用户和评论功能是质量评估中最常用的,而用户标准和数据功能的重要性在整个知识领域中是可变的。在主要包含自助问题的技术问答站点中,实用程序类是最常用的条件组。社会情感类的流行在诸如艺术和娱乐之类的以讨论为导向的主题类别中更加明显,人们可以在其中寻求他人的意见或建议。 Stack Exchange中的艺术和娱乐问答网站的用户似乎在回答者的努力和时间,良好的态度或举止,个人经验和相同品味上给予了更多重视。观察到用户功能的重要性以及在科学问答网站上对答卷人专业知识的重视。检查知识质量范围内用户质量标准与数据功能之间的联系或差距,可以帮助更好地了解用户对其首选答案的评估行为,并确定社交问答在用户对答案质量评估中进行教育/干预的潜力。该考试还为设计更有效的社交问答平台提供了实用指南,其中考虑了如何自定义社区支持系统,激励贡献和控制内容质量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号