Analyzing Growth Trends and Attachment Mode of Social Blog Tags
Ye Guanghui1(), Hu Jinglan1, Xu Jian2, Xia Lixin1
1School of Information Management, Central China Normal University, Wuhan 430079, China 2Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China
[Objective] This study reveals the forming mechanism of network nodes, aiming to examine the growth trend and attachment mode of social blog tags. [Methods] Firstly, we proposed the model of tag growth with the help of statistics and network analysis. Then, we established the categories of tag links and corresponding numbers, as well as summarized the connection rules of newly added tags. Finally, we defined the indicators of degree dependency and examined the probability of tag connection following preferential attachment modes. [Results] The tag growth showed the linear growth pattern and the distribution of tags had one single peak center, the shock left side and the gentle right side, which did not meet the power-law distribution. [Limitations] We did not explain the impacts of users’ tagging behaviors on the network connections. [Conclusions] Neither the “new tag-old tag” nor the “old tag-old tag” models are not fully compliant with the preferential attachment mode.
叶光辉, 胡婧岚, 徐健, 夏立新. 社交博客标签增长态势与连接模式分析*[J]. 数据分析与知识发现, 2018, 2(6): 70-78.
Ye Guanghui,Hu Jinglan,Xu Jian,Xia Lixin. Analyzing Growth Trends and Attachment Mode of Social Blog Tags. Data Analysis and Knowledge Discovery, 2018, 2(6): 70-78.
(Li Gang, Liu Guangxing, Mao Jin, et al.A Sentiment Label Extraction Method Based on Dependency Parsing[J]. Library and Information Service, 2014, 58(14): 12-20.)
doi: 10.13266/j.issn.0252-3116.2014.14.002
(Song Lingchao, Huang Kun.Research on Image Emotional Annotations Based on Social Tags[J]. Library and Information Service, 2016, 60(21): 103-112.)
doi: 10.13266/j.issn.0252-3116.2016.21.014
(Yang Zunqi, Zhao Jinjun.Structure and Interaction: The User Category Tags on the Sina Microblog[J]. Journal of Intelligence, 2014, 33(4): 122-127.)
doi: 10.3969/j.issn.1002-1965.2014.04.022
(Ye Guanghui, Li Gang.Structure Analysis on Semantic Social Network Based on MetaFilter[J]. Information Studies: Theory & Application, 2015, 38(12): 57-63.)
doi: 10.16353/j.cnki.1000-7490.2015.12.012
[9]
Chen J, Feng S, Liu J.Topic Sense Induction from Social Tags Based on Non-negative Matrix Factorization[J]. Information Sciences, 2014, 280: 16-25.
doi: 10.1016/j.ins.2014.04.048
[10]
Pan W, Chen S, Feng Z.Automatic Clustering of Social Tag Using Community Detection[J]. Applied Mathematics & Information Sciences, 2013, 7(2): 675-681.
doi: 10.12785/amis/070235
[11]
Chelmis C, Prasanna V K.Social Link Prediction in Online Social Tagging Systems[J]. ACM Transactions on Information Systems, 2013, 31(4): 1-27.
doi: 10.1145/2516891
[12]
Naseri S, Bahrehmand A, Ding C, et al.Enhancing Tag-based Collaborative Filtering via Integrated Social Networking Information[C]//Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. IEEE, 2013: 760-764.
(Yi Ming, Mao Jin, Deng Weihua.Fine-grained User Preference Modeling Based on Tag Networks[J]. New Technology of Library and Information Service, 2011(4): 35-41.)
[14]
Tu H, Wang X.Mining Users’ Interest Graph in Social Networks with Topic Based Tag Propagation[C]//Proceedings of IET International Conference on Smart and Sustainable City. IET, 2014: 282-285.
(Yi Ming, Wang Xuedong, Deng Weihua.Social Labeling Network Analysis and Personalized Information Service Research Based on Social Network Analysis[J]. Journal of Library Science in China, 2010, 36(2): 107-114.)
(Yi Ming, Mao Jin, Deng Weihua, et al.Evolution of Knowledge Push Network Based on Social Network in Social Tagging System[J]. Journal of Library Science in China, 2014, 40(2): 50-66.)
[17]
Ma H, Jia M, Zhang D, et al. Combining Tag Correlation and User Social Relation for Microblog Recommendation[J]. Information Sciences, 2017, 385-386(C): 325-337.
doi: 10.1016/j.ins.2016.12.047
(Cai Guoyong, Lin Hang, Wen Yimin.Study on Label Propagation Based Community Detection Algorithm for Social Semantic Network[J]. Computer Science, 2013, 40(2): 53-57.)
[19]
李栋. 在线社会网络中信息扩散研究[D]. 哈尔滨: 哈尔滨工业大学, 2014.
[19]
(Li Dong.Research of Information Diffusion in Online Social Networks[D]. Harbin: Harbin Institute of Technology, 2014.)
(Song Li.Study on Label Communication Phenomenon in the Hot Events of Public Opinion——Take “Sencond Genenration Phenomenon” as an Example[D]. Harbin: Heilongjiang University, 2016.)
(Zha Xianjin, Lv Bin.Study on the Behaviour of Social Tagging from the Aspect of Knowledge Sharing: An Empirical Analysis Based on Tags[J]. Library Tribune, 2010, 30(6): 76-81.)
(Zheng Huizhong, Zuo Wanli.Multi-labeled Social Networks Users Personality Prediction Based on Information Gain and Semantic Features[J]. Journal of Jilin University: Science Edition, 2016, 54(3): 561-568.)
doi: 10.13413/j.cnki.jdxblxb.2016.03.28
(Ye Guanghui, Xia Lixin, Li Gang, et al.Bradford’s Law Confirmatory Analysis of Social Blog Tag Distribution[J]. Journal of the China Society for Scientific and Technical Information, 2018, 37(1): 76-85.)
[24]
邱均平. 信息计量学[M]. 武汉: 武汉大学出版社, 2007: 43-222.
[24]
(Qiu Junping.Informetrics[M]. Wuhan: Wuhan University Press, 2007: 43-222.)
[25]
Yule G U.A Mathematical Theory of Evolution, Based on the Conclusions of Dr. J. C. Willis, F. R. S[J]. Philosophical Transactions of the Royal Society of London(Series B), 1925, 213: 21-87.
doi: 10.1098/rstb.1925.0002
(Su Fangli, Li Jiang.Review on the Mechanism of Link Degree Distribution——Preferential Attachment and Uniform Attachment[J]. Journal of Intelligence, 2010, 29(10): 167-171.)
doi: 10.3969/j.issn.1002-1965.2010.10.038