Research on Collaborative Tagging Behavior Mechanisms Based on Collective Intelligence Theory Based on Douban Movie Tag Data
Yi Ming1, Feng Cuicui1, Mo Fuchuan1, Deng Weihua2
1.School of Information Management, Central China Normal University, Wuhan 430079 2.School of Public Management, Huazhong Agricultural University, Wuhan 430070
易明, 冯翠翠, 莫富传, 邓卫华. 基于群体智慧理论的协同标注信息行为机理研究——以豆瓣电影标签数据为例[J]. 情报学报, 2021, 40(1): 101-114.
Yi Ming, Feng Cuicui, Mo Fuchuan, Deng Weihua. Research on Collaborative Tagging Behavior Mechanisms Based on Collective Intelligence Theory Based on Douban Movie Tag Data. 情报学报, 2021, 40(1): 101-114.
1 Steels L. Collaborative tagging as distributed cognition[J]. Pragmatics & Cognition, 2006, 14(2): 287-292. 2 Vo? J. Tagging, folksonomy & co-renaissance of manual indexing?[OL]. (2009-04-02) [2019-11-27]. http://arxiv.org/pdf/cs/0701072v2. 3 马费成, 张斌. 图书标注环境下用户的认知特征[J]. 中国图书馆学报, 2014, 40(1): 4-14. 4 Sinha S. A cognitive analysis of tagging[EB/OL]. [2019-11-27]. http://rashmisinha.com/2005/09/27/a-cognitive-analysis-of-tagging/. 5 Heckner M, Neubauer T, Wolff C. Tree, funny, to read, Google: What are tags supposed to achieve? A comparative analysis of user keywords for different digital resource types[C]// Proceedings of the 2008 ACM Workshop on Search in Social Media. New York: ACM Press, 2008: 3-10. 6 Choi Y, Syn S Y. Characteristics of tagging behavior in digitized humanities online collections[J]. Journal of the Association for Information Science and Technology, 2016, 67(5): 1089-1104. 7 Doerfel S, Zoller D, Singer P, et al. What users actually do in a social tagging system: a study of user behavior in bibSonomy[J]. ACM Transactions on the Web, 2016, 10(2): Article No. 14. 8 Angst C M, Agarwal R. Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion[J]. MIS Quarterly, 2009, 33(2): 339-370. 9 林鑫, 周知. 用户认知对标签使用行为的影响分析——基于电影社会化标注数据的实证分析[J]. 情报理论与实践, 2015, 38(10): 85-88. 10 林鑫, 梁宇. 用户社会化标注中非理性行为的表现及原因分析[J]. 数字图书馆论坛, 2016(12): 48-53. 11 谢佳琳, 张晋朝. 高校图书馆用户标注行为研究——以信息系统成功模型为视角[J]. 图书馆论坛, 2014, 34(11): 87-93. 12 罗琳, 杨洋. 社会化标注系统中用户标签使用行为影响因素研究[J]. 图书情报知识, 2018(3): 85-94. 13 张树人. 从社会性软件、Web 2.0到复杂适应信息系统研究[D]. 北京: 中国人民大学, 2006. 14 叶光辉, 夏立新, 李纲, 等. 社交博客标签分布的布拉德福定律验证分析[J]. 情报学报, 2018, 37(1): 76-85. 15 Cress U, Held C, Kimmerle J. The collective knowledge of social tags: Direct and indirect influences on navigation, learning, and information processing[J]. Computers & Education, 2013, 60(1): 59-73. 16 牛明坤. 基于大众标注的群体知识组织性质与结构研究[D]. 长沙: 湖南大学, 2017. 17 白劲波. 基于社会化标注的群体知识形成机理及机制研究[D]. 哈尔滨: 哈尔滨工程大学, 2014. 18 Surowiecki J. The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations[M]. New York: Random House, 2004. 19 黄晓斌, 周珍妮. Web 2.0环境下群体智慧的实现问题[J]. 图书情报知识, 2011(6): 113-119. 20 Nishimoto K, Sumi Y, Mase K. Enhancement of creative aspects of a daily conversation with a topic development agent[C]// Proceedings of the Annual Asian Computing Science Conference on Coordination Technology for Collaborative Applications. Heidelberg: Springer, 1998: 63-76. 21 Nunaneker Jr J F, Romano Jr N C, Briggs R O. A framework for collaboration and knowledge management[C]// Proceedings of the 34th Annual Hawaii International Conference on System Sciences. IEEE, 2001: 1-12. 22 甘永成, 祝智庭. 虚拟学习社区知识建构和集体智慧发展的学习框架[J]. 中国电化教育, 2006(5): 27-32. 23 Lykourentzou I, Papadaki K, Vergados D J, et al. CorpWiki: A self-regulating wiki to promote corporate collective intelligence through expert peer matching [J]. Information Sciences, 2010, 180(1): 18-38. 24 赵芳, 李林红. 群体智慧在复杂网络认知系统中的涌现——以滇池流域可持续发展为例[J]. 科技进步与对策, 2010, 10(10): 20-23. 25 Hong H, Ye Q, Du Q Z, et al. Crowd characteristics and crowd wisdom: Evidence from an online investment community[J]. Journal of the Association for Information Science and Technology, 2020, 71(4): 423-435. 26 吴增源, 周彩虹, 易荣华, 等. 开放式创新社区集体智慧涌现的生态演化分析——基于知识开放视角[J/OL]. 中国管理科学. (2019-12-12) [2019-12-25]. https://doi.org/10.16381/j.cnki.issn1003-207x.2019.0916. 27 Li X, Qin Z F, Kar S. Mean-variance-skewness model for portfolio selection with fuzzy returns[J]. European Journal of Operational Research, 2010, 202(1): 239-247. 28 Lee S, Ha T, Lee D, et al. Understanding the majority opinion formation process in online environments: an exploratory approach to Facebook[J]. Information Processing & Management, 2018, 54(6): 1115-1128. 29 Joanes D N, Gill C A. Comparing measures of sample skewness and kurtosis[J]. Journal of the Royal Statistical Society: Series D (the Statistician), 1998, 47(1): 183-189. 30 Chow G C. Tests of equality between sets of coefficients in two linear regressions[J]. Econometrica, 1960, 28(3): 591-605. 31 Langley D J, Hoeve M C, Ortt J R, et al. Patterns of herding and their occurrence in an online setting[J]. Journal of Interactive Marketing, 2014, 28(1): 16-25. 32 马费成, 夏永红. 网络信息的生命周期实证研究[J]. 情报理论与实践, 2009, 32(6): 1-7. 33 柯平. 迎接下一代情报学的诞生——情报学的危机与变革[J]. 情报科学, 2020, 38(2): 3-10.