图书情报工作 ›› 2019, Vol. 63 ›› Issue (8): 38-44.DOI: 10.13266/j.issn.0252-3116.2019.08.006

• 理论研究 • 上一篇    下一篇

网络学习社区用户答案认可度的影响机理研究

陈娟1, 邓胜利2   

  1. 1. 华中农业大学公共管理学院信息管理系, 武汉 430070;
    2. 武汉大学信息管理学院, 武汉 430072
  • 收稿日期:2018-07-04 修回日期:2018-10-12 出版日期:2019-04-20 发布日期:2019-04-20
  • 作者简介:陈娟(ORCID:0000-0003-1762-4074),副教授,硕士生导师,E-mail:chenjuan@mail.hzau.edu.cn;邓胜利(ORCID:0000-0001-7489-4439),教授,博士生导师。
  • 基金资助:
    本文系教育部人文社会科学重点研究基地重大项目"我国服务业信息化推进与保障机制研究"(项目编号:15JJD870001)和中央高校基本科研业务费专项基金(项目编号:2662018PY095)研究成果之一。

Research on the Influencing Mechanism of Users' Recognition of Answers in E-learning Community

Chen Juan1, Deng Shengli2   

  1. 1. Department of Information Management, College of Public Administration, Huazhong Agricultural University, Wuhan 430070;
    2. School of Information Management, Wuhan University, Wuhan 430072
  • Received:2018-07-04 Revised:2018-10-12 Online:2019-04-20 Published:2019-04-20

摘要: [目的/意义]研究用户答案认可度的影响机理有助于识别中心路径和边缘路径,留存高影响力用户,保障高质量问答,增加社区活跃度。[方法/过程]构建影响答案认可度的理论模型,采集人大经济论坛上1 964条帖子数据,运用Smartpls软件对数据进行分析。[结果/结论]用户活跃度可以分别影响个人影响力和答案质量,进而影响答案认可度,答案质量也会对个人影响力造成影响。个人影响力对答案认可度的影响程度远远超过答案质量对答案认可度的影响,亦即边缘路径比中心路径的影响程度更大。

关键词: 网络学习社区, 用户影响力, 答案认可度, 影响机理

Abstract: [Purpose/significance] Study of the influencing mechanism of users' recognition of answers is helpful to identify central path and edge path, to retain users with high influence power, to guarantee high quality questions and answers, then to increase community activity.[Method/process] After building a theoretical model about answer recognition, collecting data from 1964 posts on the NPC Economic Forum, Smartpls software is used to analyze the data.[Result/conclusion] User activity can affect user influence and answer quality separately, thus affecting the degree of answer recognition in E-learning communities. Answer quality affects user influence as well. The impact of user influence power on answer recognition is far more than that of answer quality, that is, the edge path has a greater impact than the central path.

Key words: e-learning community, user influence, answer recognition degree, influence mechanism

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