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社会化问答知识分享用户感知有用性影响因素研究——以知乎为例
引用本文:李进华,张婷婷.社会化问答知识分享用户感知有用性影响因素研究——以知乎为例[J].现代情报,2018,38(4):20-28.
作者姓名:李进华  张婷婷
作者单位:华中师范大学信息管理学院, 湖北 武汉 430079
基金项目:国家社会科学基金项目"语义网络环境下面向数字化科研的分布式知识发现研究"(项目编号:11BTQ040)。
摘    要:目的/意义]社会化问答社区的投票机制有利于信息消费者筛选高质量回答。本文以用户原创回答为研究对象,探讨影响知识分享用户感知有用性的影响因素。方法/过程]以信息接受模型为基础,基于知乎社区71 495条回答,结合文本分析与负二项回归分析方法,从回答特征、回答质量和回答者特征3个方面探讨知识分享有用性的影响因素。结果/结论]研究结果表明,回答特征(及时性、图片或引用)、回答质量(答案中心度、情感支持)、回答者特征(社会网络中心度、可信度)均对回答有用性投票具有正向影响。回答的语言多样性对回答有用性投票具有负向影响。本研究通过实证进行客观分析,有利于促进回答者贡献高质量回答并对社会化问答社区进行高质量的信息服务提供可行性建议。

关 键 词:知识分享  用户感知有用性  信息接受模型  知乎社区  

Research on Influencing Factors of User Perceived Usefulness of Knowledge Sharing in Social Q&A——A Case Study of Zhihu
Authors:Li Jinhua  Zhang Tingting
Institution:School of Information Management, Central China Normal University, Wuhan 430079, China
Abstract:Purpose/Signficance]The voting mechanism of social Q&A community is helpful for information consumers to select high quality answers.This paper focused on the original knowledge sharing of users in social Q&A community,and explored the factors that influence the user perceived usefulness of knowledge sharing.Method/Process]Based on the information adoption model and 71495 answers in social Q&A community,combining text analysis and negative binomial regression analysis,this paper discussed the influencing factors of knowledge sharing usefulness from three aspects of answer characteristics,answer quality and respondent characteristics.Result/Conclusion]The results showed that the answer characteristics(timeliness,pictures or citations),answer quality(answer centrality,emotional support),respondent characteristics(social network centrality,credibility)had a positive impact on answer useful votes.However,the linguistic diversity of answers had a negative effect on answer useful votes.And this research promoted the sharers to contribute high quality knowledge sharing and provides feasible suggestions for high quality information service in social Q&A community.
Keywords:knowledge sharing  user perceived usefulness  information acceptance model  zhihu community  
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