健康问答社区用户知识共享网络动态演化研究
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摘要
【目的/意义】研究健康问答社区中用户知识共享网络动态演化的特征及规律,对社区的有效管理和持续发展具有重要意义。【方法/过程】本文选取慢友帮糖尿病互助圈用户数据,构建用户知识共享网络,对网络进行时间切片分析,从整体网、子群两个层面进行动态演化及动力机制分析。【结果/结论】研究表明,在整体网分析中,随着社区发展,活跃用户数量先增加后降低、网络凝聚力先降低后升高;在子群分析中,知识接收者在子群形成过程中有明显的优势;而随着社区发展到中后期,各个子群形态开始分化,出现知识接收者主导型、知识提供者主导型和均衡型子群。
【Purpose/significance】Finding regulations and reasons of user knowledge sharing network evolution is important for effective management and continuous development of Health Community of Question and Answer(HCQA).【Method/process】This paper collected user data of diabetes groups in Man Youbang to construct user knowledge sharing network. Then, dynamic evolution regulations and mechanism in terms of the whole network and subgroups were studied bytime slice analysis.【Result/conclusion】The study found that at first the whole network density decreases and later raiseswith change of stage. And in subgroup analysis, the knowledge receivers perform better and there appear knowledge-receiver-oriented, knowledge-provider-oriented and balanced subgroups in the middle and later stages of community development.
【Purpose/significance】Finding regulations and reasons of user knowledge sharing network evolution is important for effective management and continuous development of Health Community of Question and Answer(HCQA).【Method/process】This paper collected user data of diabetes groups in Man Youbang to construct user knowledge sharing network. Then, dynamic evolution regulations and mechanism in terms of the whole network and subgroups were studied bytime slice analysis.【Result/conclusion】The study found that at first the whole network density decreases and later raiseswith change of stage. And in subgroup analysis, the knowledge receivers perform better and there appear knowledge-receiver-oriented, knowledge-provider-oriented and balanced subgroups in the middle and later stages of community development.
引文
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2 孙康,杜荣.实名制虚拟社区知识共享影响因素的实证研究[J].情报杂志,2010,29(4):83-87.
3 Zhang Z,Li Q,Zeng D,et al. Extracting evolutionary communities in community question answering[J].Journal of the Association for Information Science and Technology,2014,65(6):1170-1186.
4 Lin J W,Mai L J,Lai Y C. Peer interaction and social network analysis of online communities with the support of awareness of different contexts[J].International Journal of Computer-Supported Collaborative Learning,2015,10(2):139-159.
5 Moliner L A,Gallardo-Gallardo E,de Puelles P G. Understanding scientific communities:a social network approach to collaborations in Talent Management research[J].Scientometrics,2017,113(3):1439-1462.
6 邓胜利,向阳.基于学术社交网络的文献阅读及学科关注点差异研究[J].图书情报工作,2017,61(6):99-106.
7 Colladon A F,Vagaggini F. Robustness and stability of enterprise intranet social networks:The impact of moderators[J].Information Processing&Management,2017,53(6):1287-1298.
8 Barbosa M W,Ladeira M B,de la Calle Vicente A. An analysis of international coauthorship networks in the supply chain analytics research area[J].Scientometrics,2017,111(3):1703-1731.
9 Ferrara M,Mavilia R,Pansera B A. Extracting knowledge patterns with a social network analysis approach:an alternative methodology for assessing the impact of power inventors[J].Scientometrics,2017,113(3):1593-1625.
10 吴江,周露莎.在线医疗社区中知识共享网络及知识互动行为研究[J].情报科学,2017,35(3):144-151.
11 Cainelli G,Maggioni M A,Uberti T E,et al. The strength of strong ties:How co-authorship affect productivity of academic economists?[J].Scientometrics,2015,102(1):673-699.
12 韩文,刘畅,雷秋雨.分析学术社交网络对科研活动的辅助作用——以ResearchGate和Academia.edu为例[J].情报理论与实践,2017,40(8):105-111.
13 李裕广.在线医疗社区患者医疗信息共享意愿影响因素研究[D].哈尔滨:哈尔滨工业大学,2015.