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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (6): 70-78    DOI: 10.11925/infotech.2096-3467.2017.1311
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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
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Abstract  

[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.

Key wordsSocial Blog Tag      Growth Trend      Attachment Mode      Social Network      Preferential Attachment      Degree Dependency     
Received: 22 December 2017      Published: 11 July 2018
ZTFLH:  G350  

Cite this article:

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.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1311     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I6/70

时刻 年份 非重复标签数量(个)
0 2006 2 057
1 2007 2 686
2 2008 4 069
3 2009 5 488
4 2010 6 967
5 2011 7 779
6 2012 8 397
7 2013 8 838
8 2014 9 145
9 2015 9 465
10 2016 9 737
配对样本 样本数 相关
系数
相关
显著度p1
t t检验
显著度p2
对1-2013&2014 988 0.926 0.000 -19.410 0.000
对2-2014&2015 988 0.961 0.000 -16.516 0.000
对3-2015&2016 988 0.976 0.000 -13.982 0.000
标签增长(Ⅰ) 标签增长(Ⅱ) 标签增长(Ⅲ) 标签增长(Ⅰ-Ⅲ)
不变 33.7% 33.2% 42.7% 24.5%
变大 66.3% 66.8% 57.3% 75.5%
2013 2014 2015 2016
2013 Pearson 相关性 1 0.926** 0.843** 0.777**
显著性(双侧) 0.000 0.000 0.000
2014 Pearson 相关性 0.926** 1 0.961** 0.913**
显著性(双侧) 0.000 0.000 0.000
2015 Pearson 相关性 0.843** 0.961** 1 0.976**
显著性(双侧) 0.000 0.000 0.000
2016 Pearson 相关性 0.777** 0.913** .976** 1
显著性(双侧) 0.000 0.000 .000
年度 标签增长阶段 Pearson相关性 显著性(双侧)
2013 (Ⅰ) -0.094** 0.003
2014 (Ⅱ) -0.100** 0.002
2015 (Ⅲ) -0.049 0.124
2016 (Ⅰ-Ⅲ) -0.146** 0.000
标签关系
时间
新标签-新标签 新标签-旧标签 旧标签-旧标签
2013-2014 4 611 17 616 31 060
2013-2015 3 372 18 140 59 821
2013-2016 4 038 21 213 88 045
标签连接概率
时间
新标签-新
标签
新标签-旧标签 旧标签-旧标签
建立 强化
2013-2014 0.029 0.971 0.153 0.847
2013-2015 0.026 0.974 0.481 0.519
2013-2016 0.050 0.950 0.321 0.679
均值 0.035 0.965 0.318 0.682

标签连接模式
时间
新标签-旧标签 旧标签-旧标签
优先连接 非优先
连接
优先连接 非优先
连接
2013-2014 7 439 10 120 14 294 38 993
2013-2015 5 730 12 354 21 758 59 575
2013-2016 6 233 14 856 25 582 87 714
均值 6 467 12 443 20 545 62 094
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