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作 者:程秀峰[1] 张梦圆 丁芬 陆颖颖[1] Cheng Xiufeng;Zhang Mengyuan;Ding Fen;Lu Yingying(School of Information Management,Central China Normal University,Wuhan 430079,China)
机构地区:[1]华中师范大学信息管理学院,湖北武汉430079
出 处:《现代情报》2022年第7期114-124,共11页Journal of Modern Information
基 金:国家自然科学基金面上项目“基于情境感知的智慧图书馆阅读与交流服务实现路径研究”(项目编号:71974069);国家自然科学基金面上项目“信息生命周期视角下教育大数据隐私泄露的风险评估与追溯消解机制研究”(项目编号:61977036)。
摘 要:[目的/意义]对开发者社区中意见领袖行为数据进行分析,解释这些特征值对其他用户行为的影响力,探究意见领袖影响力形成的原因,为提升该类社区用户参与度提供最佳实践路径。[方法/过程]依据社区的综合排名,筛选出意见领袖,将他们的特征分成3类(成就、互动、贡献),基于每类特征值对意见领袖进行聚类(权威型、新晋型、传播型),利用网络结构可视化方法揭示意见领袖的影响力要素,并从用户发展、平台建设及机构资源利用3个视角提供参考建议。[结果/结论]可以通过这种方式动态确定特征值分布对关键用户提升影响力的最佳路径。典型开发者社区中权威型意见领袖的粉丝数、原创数特征,传播型意见领袖的等级值、原创数特征,新晋型意见领袖的收藏数、码龄、博客数等特征,对用户学习意愿的影响较大。[Purpose/Significance]Analyzing the behavior data of opinion leaders in the developer community,explaining the influence of behavioral characteristics values on other users behaviors,exploring the reasons for the formation of opinion leaders influence,and providing the best practice path for improving user participation in such communities.[Method/Process]Firstly,opinion leaders were selected according to the comprehensive ranking of the community.Then,the characteristics were classified into three categories(achievement,interaction and contribution);Then,the opinion leaders were clustered based on the values of each category(authoritative,upstart,dissemination).Finally,the network structure visualization method was used to reveal the influence factors of opinion leaders,and suggestions were provided from the perspectives of user development,platform construction and institutional resource utilization.[Result/Conclusion]In this way,the optimal path of eigenvalue distribution to enhance the influence of key users can be determined dynamically.In the typical developer community,the characteristics of authoritative opinion leaders number of fans and originality,the grade value and originality of communication opinion leaders,and the collection number,code age and blog number of newly emerging opinion leaders have a great influence on users learning intention.
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