作　　者： ;

机构地区： 广西师范大学经济管理学院

出　　处： 《武汉理工大学学报（信息与管理工程版）》 2023年第4期589-593,共5页

摘　　要： 基于细分的用户集体性语言风格和以行为频次衡量的表现用户在社区中的参与程度,建立综合模型,证实了用户集体性语言风格、参与程度与用户领先性的正向关系。现有文献在以用户内容信息表现集体性语言风格上,宽泛使用集体性概念,导致集体性语言风格与用户领先性的正向关系不显著。因此,将领先用户的集体性语言风格细分为高认同度、分享精神和帮助,同时加入行为频次表现用户在社区中的参与程度,建立模型,并通过数据挖掘获得在线社区中365名用户的数据。结果表明,内容信息中分享语言风格与用户领先性正相关,帮助语言风格与用户领先性的关系不显著,高认同度语言风格与用户领先性负相关;参与程度指标中主题帖数和勋章数与用户领先性正相关,为领先用户智能识别提供了实证支持。 Based on the subdivided user's collective language style and the frequency of user's participation degree in the community,a comprehensive model was established to confirm the positive relationship between user's collective language style,participation and lead-userness.In terms of the collective language style of user content information,the collective concept was widely used in the existing literature,which leaded to the positive relationship between collective language style and user leadership is not significant.Therefore,the lead user's collective language style was subdivided into high identification,sharing spirit and help,as well as the behavior frequency was added to express the user's participation level in the community,and the model was established.While the data of 365 users in the online community was obtained through data mining.The results show that the shared language style in the content information is positively correlated with the lead-userness,the relationship between the help language style and the lead-userness is not significant,and the high recognition language style is negatively correlated with the lead-userness.The number of topic posts and medals in the participation index is positively correlated with the lead-userness,which provides empirical support for the intelligent identification of leading users.

关 键 词： 用户集体性语言风格 用户领先性 数据挖掘 用户参与 创新社区

领　　域： [经济管理—管理学]