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作 者:严炜炜[1,2] 王清烨 张敏[1,2] Yan Weiwei;Wang Qingye;Zhang Min(School of Information Management,Wuhan University,Hubei Wuhan 430072;Center for E-commerce Research and Development,Wuhan University,Hubei Wuhan 430072)
机构地区:[1]武汉大学信息管理学院,湖北武汉430072 [2]武汉大学电子商务研究与发展中心,湖北武汉430072
出 处:《情报理论与实践》2024年第7期97-106,共10页Information Studies:Theory & Application
基 金:国家自然科学基金面上项目“情境意识驱动的跨平台知识交流行为及其价值共创研究”(项目编号:72374159);中央高校基本科研业务费专项资金资助项目“多元社区情境下用户知识交流价值识别与共创研究”(项目编号:2042023kf0173)的成果。
摘 要:[目的/意义]从知识交流生态视角出发,探究基于视频资源的用户跨平台知识交流行为偏好规律,为用户利用多平台开展交互、实现高价值知识交流提供有效指导。[方法/过程]通过对齐在B站和微博上进行跨平台知识交流的用户,并获取他们在两个平台发布的全量视频内容7215条和同质化视频的330367条评论文本,基于知识生态系统框架,分别针对知识生产者和知识分解者进行内容发布和评论互动等跨平台知识交流偏好的探究。[结果/结论]知识生产者会在不同平台规律性地发布同质化视频以获得知识消费者更好的互动反馈,且根据平台定位和平台功能差异进行标题差异化展示;跨平台知识交流中,知识分解者的评论互动偏好与平台特性相关。[局限]仅选择B站和微博中高影响力知识生产者群体进行研究,后续研究中可对更为多元的知识交流平台以及更丰富的大众知识生产者行为规律进行拓展分析。[Purpose/significance]From the perspective of knowledge exchange ecology,this paper explores the preferences of users’cross-platform knowledge exchange behavior based on video resources,so as to provide effective guidance for users to carry out interaction on multiple platforms and realize high-value knowledge exchange.[Method/process]By aligning users who conduct cross-platform knowledge exchange on Bilibili and Weibo,and obtaining 7215 full video content,330367 comment texts of indicators and homogenized videos published by them on the two platforms,based on the knowledge ecosystem framework,cross-platform knowledge exchange preferences such as content publishing and comment interaction were explored for knowledge producers and knowledge dissolvers respectively.[Result/conclusion]Knowledge producers publish homogenized videos regularly on different platforms to obtain better interactive feedback from knowledge consumers,and display titles differently according to platform positioning and platform function differences.Comment interaction preferences of knowledge disaggregators in cross-platform knowledge exchange are related to platform characteristics.[Limitations]The limitation of this paper is that only the high-influence knowledge producer groups in Bilibili and Weibo are selected for the study,and the behavioral patterns of more diversified popular knowledge producers in different platforms can be expanded and analysed in subsequent studies.
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