情报科学 ›› 2022, Vol. 39 ›› Issue (1): 176-183.

• 博士论坛 • 上一篇    下一篇

基于扎根理论的虚拟学术社区用户参与行为研究——以小木虫为例 

  

  • 出版日期:2022-01-01 发布日期:2022-01-13

  • Online:2022-01-01 Published:2022-01-13

摘要: 【目的/意义】虚拟学术社区的发展离不开用户参与,研究分析虚拟学术社区当中用户参与行为类型,对于
促进虚拟学术社区用户之间的知识交流具有一定的启发价值。【方法
/过程】依据扎根理论,对小木虫虚拟学术社区
进行数据采集,将用户分为初级用户、中级用户以及高级用户三个等级,搜集了小木虫论坛热门博客栏目下,回复
大于
10的帖子内容,利用质性分析软件 NVIVO12.0对其进行开放式、主轴式和选择性编码,并据此构建虚拟学术
社区参与行为的模型。【结果
/结论】根据编码结果显示,用户在虚拟学术社区参与行为总共可以分为问候欢迎、调
节规范、协助、欣赏、同情、抱怨、庆祝和交际
8种类型,不同等级的用户的参与行为具有不同的特点,在实际参与过
程当中应当强化每种用户的角色,为虚拟学术社区的未来发展提供强大助力。【创新
/局限】虽然数据来源较为单
一,但是本文将扎根理论引入虚拟学术社区的研究中,完善了该情境下用户参与行为的分类体系,对现有研究成果
进行补充。

Abstract: Purpose/significanceThe development of virtual academic community is inseparable from user participation. The re⁃
search and analysis of user participation behavior types in virtual academic community have certain enlightening value for promoting knowledge exchange among users of virtual academic community.
Method/processBased on the grounded theory, data collection is carried out on the Xiaomuchong community, and users are divided into three levels: elementary, intermediate, and advanced. Data was collected from the popular column, which has more than 10 posts, and the open, spindle and selective coding of the virtual academic community were carried out by using the qualitative analysis software NVIVO12.0. According to this builds a model of virtual academ⁃ic community users engagement practices.Result/conclusionAccording to the coding results, the types of virtual academic commu⁃nity users' engagement practices include greeting, regulating, assisting, appreciating, empathizing, complaining, celebrating and min⁃gling. The participation behavior of different users has different characteristics, in the actual participation process, each user's role should be strengthened to provide a powerful boost for the future development of the virtual academic community.Innovation/limita⁃tionAlthough the data sources are relatively limited, this paper introduces the grounded theory into the research of virtual academic communities, improves the classification system of user participation behavior in this context, and supplements the existing research results.