用户交互对社会标注行为的差异影响研究——以豆瓣网为例

doi:10.13266/j.issn.0252-3116.2020.20.013

图书情报工作 ›› 2020, Vol. 64 ›› Issue (20): 117-128.DOI: 10.13266/j.issn.0252-3116.2020.20.013

用户交互对社会标注行为的差异影响研究——以豆瓣网为例

庄倩¹, 骆慧颖^1,2, 戴岽丞¹, 刘丽霞¹, 靳雪宁¹

1 南京农业大学信息科学技术学院南京 210095;
2 北京师范大学系统科学学院北京 100875

收稿日期:2020-04-13 修回日期:2020-06-17 出版日期:2020-10-20 发布日期:2020-10-20
作者简介:庄倩(ORCID:0000-0002-0984-4723),讲师,博士,E-mail:zhuangqian@njau.edu.cn;骆慧颖(ORCID:0000-0003-4587-9509),本科生;戴岽丞(0000-0003-2923-9640),本科生;刘丽霞(0000-0002-6310-2157),本科生;靳雪宁(0000-0002-1331-7440):本科生。
基金资助:
本文系南京农业大学中央高校基本科研业务费专项资金"多元化视角的用户标注行为及影响因素研究"（项目编号：KYZ201864）和南京农业大学2018年国家大学生创新训练计划项目"豆瓣用户标注行为差异性研究"（项目编号：20181037077）研究成果之一。

Research on the Influence of User Interaction on the Difference of Social Tagging Behaviors——A Case Study of Douban.com

Zhuang Qian¹, Luo Huiying^1,2, Dai Dongcheng¹, Liu Lixia¹, Jin Xuening¹

1 College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095;
2 School of Systems Science, Beijing Normal University, Beijing 100875

Received:2020-04-13 Revised:2020-06-17 Online:2020-10-20 Published:2020-10-20

摘要/Abstract

摘要： [目的/意义] 为提高标签质量，优化社会标注系统的信息服务提供依据，从用户在社会标注系统中与其他用户交互的视角，探讨不同交互特征用户的标注行为差异。[方法/过程] 以豆瓣读书作为社会标注系统研究样本，从标签数量、标签结构、标签语义、标注动机和活跃度五个角度研究豆瓣用户标注行为的分布特征；使用用户的关注人数、被关注人数和使用年限表征其在社会标注系统中与其他用户的关联和交互程度，通过差异性分析探讨不同交互特征用户标注行为的差异，并通过多元回归分析研究交互特征对这种差异影响的程度。[结果/结论] 实证研究表明，不同交互特征的用户间的社会标注行为存在显著差异：与其他用户交互比较强的用户标签数据集包含更多的标签，关注其他用户越多的用户和被越多用户关注的用户所使用的标签数量越多；使用豆瓣读书年限越长的用户，其平均标签长度和标签重用率越大，而其与其他用户的关注关系对其标签平均长度和标签重用率的影响不大；用户的特殊语种标签比受用户的使用年限影响很大，但一个用户被多少人关注不会显著的影响其特殊语种标签比；关注其他用户越多的用户在标注系统中越活跃。由此可见，社会标注系统可以采取措施加强系统中用户间的交互，通过用户间的相互作用规范用户的社会标注行为，从而提高标签质量。

关键词: 用户, 交互, 标注行为, 差异性

Abstract: [Purpose/significance] From the perspective of users interacting with other users in social tagging systems, the differences in tagging behavior of users with different interaction characteristics are explored. The study is helpful to improve the quality of labels, and optimize the quality of information service of the social tagging systems.[Method/process] Using the sample data from Douban Book website, the quantitative indicators were selected to study the distribution characteristics of the users' tagging behaviors from the perspectives of number of tags, tag structure, tag semantics, tagging motivation and user activity. Three indicators including the number of users one follows, the number of one's followers and one's registered age were used to represent a user's degree of association and interaction with other users, then the differences in tagging behavior of users with different interaction characteristics were discussed through difference analysis. Moreover, the influence of the interaction characteristics on these differences were investigated through multivariate regression analysis.[Result/conclusion] The results shows that there exists significant differences in social tagging behaviors among users with different interaction characteristics:users who have stronger interactions with other users have more tags; users who have followed more users and have more followers the greater the number of tags used; the longer the user uses Douban, the greater the average tag length and tag reuse, while the relationship with other users has little effect on the average tag length and tag reuse rate; the user's ratio of tags with special language is also greatly affected by the user's registered age, but the number of user's followers does not significantly affect the user's ratio of tags with special language; the more users who follow other users, the more active they are in the tagging system. It is suggested that the social tagging system can take measures to strengthen the interaction between users, and regulate the users' social tagging behavior through the interaction between users, thereby improve the quality of the social tags in the system.

Key words: user, interaction, tagging behavior, difference

中图分类号:

G254

庄倩, 骆慧颖, 戴岽丞, 刘丽霞, 靳雪宁. 用户交互对社会标注行为的差异影响研究——以豆瓣网为例[J]. 图书情报工作, 2020, 64(20): 117-128.

Zhuang Qian, Luo Huiying, Dai Dongcheng, Liu Lixia, Jin Xuening. Research on the Influence of User Interaction on the Difference of Social Tagging Behaviors——A Case Study of Douban.com[J]. LIS, 2020, 64(20): 117-128.

参考文献

[1] TRANT J. Studying social tagging and folksonomy:a review and framework[J]. Journal of digital information, 2009, 10(1):1-42.
[2] FAROOQ U,KANNAMPALLIL TG,SONG Y,et al. Evaluating tagging behavior in social bookmarking systems:metrics and design heuristics[C]//Proceedings of the 2007 international ACM conference on supporting group work. New York:Association for Computing Machinery, 2007:351-360.
[3] MIRZAEE V,IVERSON L. Tagging:Behaviour and motivations[J]. Proceedings of the American Society for Information Science and Technology, 2009(46):1-5.
[4] WANG X, KUMAR S, LIU H. A study of tagging behavior across social media[C]//Proceeding of the 2011 workshop on social web search and mining. Beijing:SIGIR, 2011.
[5] GUYOT A. Understanding booksonomies-How and why are book taggers tagging[D]. Aberystwyth:University of Wales, 2013.
[6] GOLDER S A, HUBERMAN B A. Usage patterns of collaborative tagging systems[J]. Journal of information science, 2006, 32(2):198-208.
[7] 胡潜,石宇.图书主题对用户标签使用行为影响研究[J].图书情报工作,2016,60(8):106-112.
[8] PEESAPATI S T, WANG H C, COSLEY D. Intercultural human photo encounters:how cultural similarity affects perceiving and tagging photographs[C]//Proceedings of the 3rd international conference on intercultural collaboration. New York:Association for Computing Machinery, 2010:203-206.
[9] DONG Z, SHI C, SEN S, et al. War * vs in forrest gump:cultural effects in tagging communities[C]//Proceedings of the sixth international AAAI conference on weblogs and social media. California:The AAAI Press, 2012:82-89.
[10] 张颖怡, 章成志, 池雪花, 等. 科研用户博文关键词标注行为差异研究——以科学网博客为例[J]. 现代图书情报技术, 2015(10):13-21.
[11] SEN S, LAM S K, et al, Tagging, community, vocabulary, evolution[C]//Proceedings of the 2006 ACM conference on computer supported cooperative work. New York:Association for Computing Machinery, 2006:181-190.
[12] ŠPIRANEC S, IVANJKO T. Experts vs. novices tagging behavior:an exploratory analysis[J]. Procedia-Social and Behavioral Sciences, 2013, 73:456-459.
[13] 查先进,吕彬.知识共享视角下的大众标注行为研究-基于标签的实证分析[J]. 图书馆论坛, 2010, 30(06):76-81.
[14] SINHA R. A cognitive analysis of tagging[EB/OL].[2020-02-25]. http://rashmisinha.com/2005/09/27/a-cognitive-analysis-of-tagging/.
[15] SZEKELY B, TORRES E. Ranking bookmarks and bistros:intelligent community and folksonomy development[EB/OL].[2020-02-23]. http://www.eliastorres.com/archives/2005/07/13/tagrank.pdf.
[16] 易明,曹高辉,毛进,等.基于Tag的知识主题网络构建与Web知识推送研究[J]. 中国图书馆学报, 2011, 37(4):4-12.
[17] 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.
[18] 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.
[19] STROHMAIER M, KÕRNER C, KERN R. Understanding why users tag:a survey of tagging motivation literature and results from an empirical study[J]. Web semantics science services & agents on the World Wide Web, 2012, 17(4):1-11.
[20] 王娜,马云飞.网络环境下大众标注行为动机的调查与分析[J].图书情报工作, 2013, 57(23):100-107.
[21] 常唯. 论网络环境下用户标注的价值与应用[J]. 图书情报工作, 2008, 52(1):9-12.
[22] 吴丹, 许小梅. 图书馆与图书分享网站的用户标注行为比较研究[J]. 图书情报知识, 2013(1):85-93.
[23] 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.
[24] 庄倩, 韩正彪. 社会标注系统质量对用户标注意愿的影响机理[J]. 图书馆论坛, 2019, 39(6):71-79.
[25] BINKOWSKI P J. The effect of social proof on tag selection in social bookmarking applications[EB/OL].[2020-03-27]. http://etd.ils.unc.edu:8080/dspace/bitstream/1901/358/1/philipbinkowski.pdf.
[26] KOWATSCH T, MAASS W. The impact of pre-defined terms on the vocabulary of collaborative indexing systems[C]//16th European conference on information systems. Galway:ECIS Standing Committee, 2008:2136-2147.
[27] COSLEY D, LAM S K, ALBERT I, et al. Is seeing believing? how recommender interfaces affect users' opinions[C]//Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York:Association for Computing Machinery, 2003:585-592.
[28] CAMERON M. Position paper, tagging, taxonomy, flickr, article, toread[EB/OL].[2020-04-20]. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.74.8883.
[29] CHOI Y, SYN S Y. Characteristics of tagging behavior in digitized humanities online collection[J]. Journal of the association for information science and technology, 2015, 27(5):1-36.
[30] 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:Association for Computing Machinery, 2008:3-10.
[31] STROHMAIER M, KÖRNER C, KERN R. Understanding why users tag:a survey of tagging motivation literature and results from an empirical study[J]. Web semantics:science, services and agents on the World Wide Web. 2012, 17(12):1-11.
[32] XU C, MA B J, CHEN X H, et al. Social tagging in the scholarly world[J]. Journal of the American Society for Information Science and Technology, 2013, 64(10):2045-2057.
[33] LEE B Z, GE S L. Personalisation and sociability of open knowledge management based on social tagging[J]. Online information review, 2010, 34(4):618-625.
[34] MENDES L H, QUIONEZ-SKINNER J, SKAGGS D. Subjecting the catalog to tagging[J]. Library Hi Tech, 2009, 27(1):30-41.
[35] CHEN C, LIN Y. What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement[J]. Telematics and informatics, 2018, 35(1):293-303.
[36] ALLEN S M, CHORLEY M, COLOMBO G B, et al. Exploiting user interest similarity and social links for micro-blog forwarding in mobile opportunistic networks[J]. Pervasive and mobile computing, 2014, 11:106-131.
[37] 邓胜利, 蒋雨婷.用户交互特征对知识付费行为预测的贡献度研究[J/OL].图书情报工作:1-10[2020-06-15]. https://doi.org/10.13266/j.issn.0252-3116.2020.08.011.
[38] STROHMAIER M,KÖRNER C,KERN R. Understanding why users tag:a survey of tagging motivation literature and results from an empirical study[J].Web semantics science services & agents on the World Wide Web,2012,17(4):1-11.
[39] 吴振宇,胡军,李德毅.社会标注系统幂律特性分析[J].复杂系统与复杂性科,2014,11(2):5-16.
[40] 李蕾, 王冕, 章成志. 区分标签类型的社会化标签质量测评研究[J]. 图书情报工作, 2013, 57(23):11-16.
[41] LI D, DING Y, QIN Z, et al. Dynamic features of social tagging vocabulary:Delicious, Flickr and YouTube[C]//2010 International Conference on Advances in Social Networks Analysis and Mining. New York:Institute of Electrical and Electronics Engineers, 2010:316-320.
[42] VANDER WAL T. Explaining and showing broad and narrow folksonomies[EB/OL].[2020-03-25]. http://www.vanderwal.net/random/entrysel.php?blog=1635.
[43] ZHOU T C, KING I. Automobile, car and BMW:horizontal and hierarchical approach in social tagging systems[C]//Proceedings of the 2nd ACM Workshop on Social Web Search and Mining. New York:Association for Computing Machinery, 2009:25-32.
[44] YIN D, XUE Z, HONG L, et al. A probabilistic model for personalized tag prediction[C]//Proceedings of the 16th ACM SIGKDD Conference on knowledge discovery and data mining. New York:Association for Computing Machinery, 2010:959-968.
[45] SIGURBJÖRNSSON B, ZWOL R V. Flickr tag recommendation based on collective knowledge[C]//Proceedings of the 17th international conference on World Wide Web. New York:Association for Computing Machinery, 2008:327-336.
[46] KIPP M E, CAMPBELL D G. Patterns and Inconsistencies in Collaborative Tagging Systems:An Examination of Tagging Practices[J]. Proceedings of the American society for information science and technology, 2007, 43(1):1-18.
[47] 吴明隆.问卷统计分析务实——SPSS操作与应用[M]. 重庆:重庆大学出版社, 2012:396-397.

用户交互对社会标注行为的差异影响研究——以豆瓣网为例

Research on the Influence of User Interaction on the Difference of Social Tagging Behaviors——A Case Study of Douban.com

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