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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (6): 69-79    DOI: 10.11925/infotech.2096-3467.2019.1104
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Identifying Key Users and Topics from Online Learning Community
Cai Yongming1(),Liu Lu1,Wang Kewei2
1Business School, University of Jinan, Jinan 250002, China
2School of Economics and Management, Inner Mongolia University of Technology, Huhhot 010051, China
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Abstract  

[Objective] This study automatically analyzes resources of a virtual learning community, aiming to address the issue of information overload. [Methods] We proposed a hyper-network LDA model based on the user-document-word cube. Then, we modified this LDA model with the help of word and user analysis. Finally, we improved the cohesiveness of topics in the hyper-network LDA model, through increasing the distribution probability of closely connected words or users for the same topics. [Results] Compared to the traditional social network analysis methods, the proposed LDA model can identify important users, key topics and the relationship among them, as well as user preferences with frequency matrix of user-vocabulary and distribution probability of user-topic. [Limitations] Hyper-network analysis theory is still developing and we only studied the weighted un-directed network, which does not include the relationship of posting and replying. [Conclusions] The hyper-network LDA model effectively analyzes topics of short texts and online interactions, which are of significance to users and online learning community managers.

Key wordsVirtual Learning Community      Hyper-Network LDA Model      Key Users      Core Topics      Joint Analysis     
Received: 08 October 2019      Published: 07 July 2020
ZTFLH:  G434 TP391  
Corresponding Authors: Cai Yongming     E-mail: cymujn@163.com

Cite this article:

Cai Yongming,Liu Lu,Wang Kewei. Identifying Key Users and Topics from Online Learning Community. Data Analysis and Knowledge Discovery, 2020, 4(6): 69-79.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2019.1104     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2020/V4/I6/69

Structure Decomposition of User-Term Hyper-Network
Decomposition Diagram of Traditional LDA Model
Decomposition Diagram of Hyper-Network LDA Model
Experimental Data
排序 用户 用户 中介中心度 用户 CLDCx,1+CLDCx,22
1 zyk20062964 93 zyk20062964 615 148.2 zyk20062964 8.728E-04
2 ydc129 62 jgchen1966 503 900.2 飞天玄舞6 8.403E-04
3 jgchen1966 61 china_cao1 433 808.2 ydc129 8.116E-04
4 widen我的世界 60 水天一色DIY 409 840.8 浪子彦青 8.040E-04
5 Crsky7 60 ydc129 346 632.8 widen我的世界 7.270E-04
6 水天一色DIY 57 420948492 344 053.3 franky_sas 6.709E-04
7 420948492 56 Crsky7 332 498.0 wangfeng666 6.309E-04
8 飞天玄舞6 52 410234198 314 516.4 我的素质低 5.884E-04
9 nightmarehelen 52 飞天玄舞6 261 111.4 tigerwolf 5.368E-04
10 wjj0913 52 浪子彦青 243 607.7 曲歌99 5.199E-04
11 资料狂人 44 kuangsir6 224 751.2 yangbenfa 4.864E-04
12 edward132 40 大家开心 222 211.5 410234198 4.264E-04
13 浪子彦青 40 梦若舞之官世强 195 902.9 nivastuli 4.110E-04
14 wwqqer 37 widen我的世界 189 873.0 数据分析闯天下 3.954E-04
15 数据分析闯天下 33 悬思苦索 184 142.5 Nicolle 3.499E-04
16 china_cao1 33 数据分析闯天下 163 175.3 wwqqer 1.770E-04
17 tigerwolf 32 davil2000 160 709.9 jjxm20060807 8.288E-05
18 劲量小兔888 30 franky_sas 156 655.9 woaiwojia9 5.793E-05
19 franky_sas 27 劲量小兔888 152 875.5 wh7064rg 4.854E-05
20 liucg9999 26 nightmarehelen 143 267.9 420948492 3.192E-05
Top20 Users of Hyper-Network Community
User Community Based on CLECC Algorithm
User-Term Sub Network of Top5 Users
Topic Distribution of Any 30 Bags of Words
Word Cloud of Forum
N Topic1 Topic2 Topic3 Topic4 Topic5 Topic6 Topic7 Topic8 Topic9 Topic10 Topic11 Topic12
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