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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (11): 80-94    DOI: 10.11925/infotech.2096-3467.2018.0293
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Studying Knowledge Dissemination of Online Q&A Community with Social Network Analysis
Wang Zhongyi1, Zhang Heming1, Huang Jing2, Li Chunya3()
1School of Information Management, Central China Normal University, Wuhan 430079, China
2Wuhan Polytechnic, Wuhan 430074, China
3School of Business, Nantong Institute of Technology, Nantong 226002,China
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Abstract  

[Objective]This paper analyzes the social network structure and knowledge dissemination mechanism of an online Q&A community, aiming to reveal the role of network nodes, and improve the learning efficiency. [Methods] First, we used the social network analysis and the entropy weight methods to describe the opinion leader’s knowledge and influence. Then, we built a knowledge dissemination model based on the Cowan model for the Q&A community. Finally, we examined the internal knowledge learning results of the network through system simulation. [Results] Ⅰ. The nodes with less knowledge had higher learning efficiency in the target network; Ⅱ. The knowledge volumes of some nodes increased rapidly, while those of the nodes with larger knowledge stock increased slowly; Ⅲ. The knowledge dissemination rate of this network has been decreasing; Ⅳ. There is strong correlation between knowledge increase and the index of knowledge and communication abilities. [Limitations] The dynamic random reconnection of network was not examined in this paper. [Conclusions] This paper offers practical advice to improve users’ learning experience in the online Q&A community.

Key wordsSocial Network Analysis      Information Entropy      Knowledge Dissemination      Cowan Model      Spongy Effect     
Received: 16 March 2018      Published: 11 December 2018
ZTFLH:  TP393  

Cite this article:

Wang Zhongyi,Zhang Heming,Huang Jing,Li Chunya. Studying Knowledge Dissemination of Online Q&A Community with Social Network Analysis. Data Analysis and Knowledge Discovery, 2018, 2(11): 80-94.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0293     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I11/80

序号 username agree followers 序号 username agree followers
01 肥肥猫 1 218 509 353 535 41 warfalcon 246 569 478 527
02 朱炫 1 128 626 579 459 42 孙志超 239 546 185 374
03 ze ran 1 029 394 207 678 43 马力 235 034 204 201
04 vczh 983 884 467 598 44 藥師 233 497 112 765
05 寺主人 940 156 454 217 45 闻佳 227 652 294 435
06 Hannibal Lecter 841 383 222 944 46 蔓玫 219 097 126 074
07 yolfilm 835 981 732 463 47 高科 218 227 505 662
08 菠菜 685 089 340 044 48 汪惟 212 827 306 975
09 孟德尔 646 872 195 376 49 pansz 208 025 212 482
10 Kaiser 635 745 277 571 50 Lightwing 202 779 132 399
11 一笑风云过 628 206 181 991 51 带三个表 199 884 312 977
12 银教授 603 600 270 015 52 沃金 196 759 118 629
13 曾加 581 484 204 864 53 李楠 190 009 415 213
14 谢熊猫君 575 400 389 782 54 张亮 187 148 697 974
15 Justin Lee 526 041 160 485 55 何明科 181 619 129 164
16 君临 483 966 182 307 56 ALEX YA 181 589 104 854
17 windleavez 463 623 106 680 57 负二 180 996 398 218
18 护耳大脸 453 444 120 567 58 小岩井 177 677 114 498
19 李松蔚 432 592 305 226 59 李暘 171 104 128 141
20 苏菲 418 907 342 303 60 葛巾 168 827 580 650
21 安雅 392 539 147 147 61 maggie 168 648 552 459
22 王路 377 760 107 665 62 Sophia 165 521 101 880
23 梁边妖 361 965 540 804 63 不鳥萬如一 160 960 397 024
24 倪一宁 360 068 153 023 64 欲三更 151 195 158 159
25 李淼 347 455 623 385 65 喻忘忧 146 550 106 649
26 极乐 344 128 114 508 66 楚沐风 146 530 119 321
27 蒋校长 341 507 152 871 67 Raymond Wang 144 990 484 481
28 动机在杭州 310 503 452 619 68 殷守甫 142 391 121 032
29 刘鹏程Sai.L 309 067 165 133 69 徐强 141 421 148 944
30 刘念 302 048 267 137 70 纽约老李校长 137 423 136 041
31 猪小宝 296 676 134 047 71 东东枪 135 709 198 629
32 徐湘楠 295 563 106 909 72 唐僧同志 133 168 126 723
33 陈章鱼 291 457 516 409 73 楠爷 131 511 129 417
34 cOMMANDO 289 557 355 508 74 覃超 118 423 123 436
35 顾扯淡 283 796 236 151 75 周晓农 118 290 481 778
36 夏吉吉 273 456 144 224 76 涛吴 116 545 182 749
37 命硬的eno 270 775 162 779 77 谭蔓茹 114 534 152 995
38 David Rand 265 537 205 266 78 Lydia 112 501 123 632
39 雷幺幺 262 207 115 092 79 李开复 108 208 981 917
40 汗青 257 863 111 979 80 夏昊BFA 101 281 197 867
序号 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20
01 0 1 1 0 0 0 0 1 0 1 1 0 0 0 1 1 0 1 0 0
02 1 0 0 0 0 0 0 1 0 1 1 1 0 1 0 0 1 0 1 0
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20 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0
字段名
username company user_id article education question thanked topic followers weibo
address job answer index_url headline agree following token sex
username answer question article agree thanked followers following topic
肥肥猫 397 89 12 1 218 509 304 153 353 535 257 11
朱炫 196 4 47 1 128 626 245 011 579 459 204 37
ze ran 2 519 0 6 1 029 394 198 023 207 678 703 137
vczh 13 688 459 46 983 884 130 151 467 598 1 841 30
寺主人 149 41 156 940 156 192 639 454 217 714 58
Hannibal Lecter 972 32 149 841 383 188 170 222 944 16 884 292
yolfilm 1 509 106 2 835 981 198 641 732 463 226 134
菠菜 1 295 19 37 685 089 190 034 340 044 536 49
孟德尔 5 096 861 47 646 872 141 033 195 376 122 8
username betweeness degree.out degree.in degree. total closeness evcent pagerank shole
肥肥猫 63.96 26 35 61 0.0076 0.1075 0.0137 36
朱炫 95.05 35 47 82 0.0081 0.1442 0.0181 52
ze ran 11.42 14 20 34 0.0069 0.0648 0.0076 21
vczh 15.67 14 20 34 0.0069 0.0589 0.0075 29
寺主人 34.57 8 35 43 0.0065 0.0737 0.0135 38
Hannibal Lecter 72.48 48 22 70 0.0091 0.1187 0.0099 51
yolfilm 94.76 29 48 77 0.0077 0.1336 0.0218 48
菠菜 120.51 43 44 87 0.0087 0.1524 0.0166 53
孟德尔 3.47 6 20 26 0.0060 0.0484 0.0074 23
answer question article agree thanked followers following topic betweeness degree.out degree.in degree.total closeness evcent pagerank shole
answer 1.00 0.39 0.12 0.29 0.12 0.17 0.09 -0.01 -0.09 -0.17 -0.06 -0.15 -0.15 -0.16 -0.05 -0.10
question 0.39 1.00 0.29 -0.02 -0.06 0.29 0.05 0.15 0.07 -0.08 0.11 -0.01 -0.09 -0.02 0.21 0.02
article 0.12 0.29 1.00 -0.07 -0.14 -0.03 0.04 0.09 0.02 -0.04 0.04 -0.01 -0.05 -0.01 0.11 -0.02
agree 0.29 -0.02 -0.07 1.00 0.92 0.20 0.14 -0.05 0.08 -0.07 0.07 -0.02 -0.06 -0.03 0.00 -0.03
thanked 0.12 -0.06 -0.14 0.92 1.00 0.24 0.13 0.01 0.16 0.03 0.15 0.10 0.04 0.09 0.08 0.07
followers 0.17 0.29 -0.03 0.20 0.24 1.00 -0.02 0.09 0.17 -0.12 0.52 0.17 -0.16 0.18 0.56 0.14
following 0.09 0.05 0.04 0.14 0.13 -0.02 1.00 0.25 0.19 0.22 -0.01 0.16 0.23 0.13 0.01 0.20
topic -0.01 0.15 0.09 -0.05 0.01 0.09 0.25 1.00 0.13 0.25 0.05 0.21 0.24 0.20 0.03 0.23
betweeness -0.09 0.07 0.02 0.08 0.16 0.17 0.19 0.13 1.00 0.76 0.66 0.88 0.73 0.85 0.65 0.81
degree.out -0.17 -0.08 -0.04 -0.07 0.03 -0.12 0.22 0.25 0.76 1.00 0.30 0.88 0.99 0.85 0.25 0.90
degree.in -0.06 0.11 0.04 0.07 0.15 0.52 -0.01 0.05 0.66 0.30 1.00 0.71 0.24 0.74 0.94 0.57
degree.total -0.15 -0.01 -0.01 -0.02 0.10 0.17 0.16 0.21 0.88 0.88 0.71 1.00 0.85 0.99 0.65 0.94
closeness -0.15 -0.09 -0.05 -0.06 0.04 -0.16 0.23 0.24 0.73 0.99 0.24 0.85 1.00 0.81 0.20 0.88
evcent -0.16 -0.02 -0.01 -0.03 0.09 0.18 0.13 0.20 0.85 0.85 0.74 0.99 0.81 1.00 0.67 0.91
pagerank -0.05 0.21 0.11 0.00 0.08 0.56 0.01 0.03 0.65 0.25 0.94 0.65 0.20 0.67 1.00 0.53
shole -0.10 0.02 -0.02 -0.03 0.07 0.14 0.20 0.23 0.81 0.90 0.57 0.94 0.88 0.91 0.53 1.00
因素 信息熵 权重 因素 信息熵 权重
answer 0.8081 0.1949 betweeness 0.9170 0.3901
question 0.6867 0.3182 degree.out 0.9527 0.2223
article 0.7665 0.2371 degree.in 0.9798 0.0949
agree 0.8935 0.1082 degree.total 0.9680 0.1506
topic 0.8607 0.1415 shole 0.9698 0.1421
用户 知识能力 传播影响力 用户 知识能力 传播影响力 用户 知识能力 传播影响力
肥肥猫 23.77 45.10 动机在杭州 9.24 64.57 何明科 9.86 20.25
朱炫 21.29 67.28 刘鹏程Sai.L 26.33 20.75 ALEX YA 2.99 44.67
ze ran 28.03 14.39 刘念 6.18 33.14 负二 19.19 98.45
vczh 70.35 17.63 猪小宝 8.56 20.75 小岩井 2.37 43.71
寺主人 24.75 27.61 徐湘楠 23.89 91.96 李暘 16.75 40.58
Hannibal Lecter 34.53 58.36 陈章鱼 15.28 20.29 葛巾 0.74 72.70
yolfilm 25.20 63.31 cOMMANDO 11.21 41.45 maggie 6.02 80.88
菠菜 16.77 77.90 顾扯淡 9.85 24.32 Sophia 1.39 31.76
孟德尔 54.34 8.34 夏吉吉 2.64 10.67 不鳥萬如一 95.00 26.46
Kaiser 11.74 44.06 命硬的eno 2.79 32.39 欲三更 12.96 86.40
一笑风云过 16.73 63.06 David Rand 12.15 13.62 喻忘忧 1.95 63.49
银教授 13.41 8.72 雷幺幺 3.66 14.68 楚沐风 2.91 23.91
曾加 12.03 71.10 汗青 12.74 80.08 Raymond Wang 8.00 53.73
谢熊猫君 13.53 57.75 warfalcon 29.78 73.38 殷守甫 1.56 18.04
Justin Lee 7.83 100.00 孙志超 26.48 19.28 徐强 8.18 8.09
君临 8.58 78.61 马力 60.21 70.62 纽约老李校长 10.31 90.03
windleavez 15.21 11.69 藥師 13.46 32.31 东东枪 11.01 35.73
护耳大脸 10.97 0.00 闻佳 4.14 38.34 唐僧同志 2.94 46.39
李松蔚 10.96 44.45 蔓玫 5.04 29.77 楠爷 3.87 43.25
苏菲 12.69 45.34 高科 6.41 10.27 覃超 9.16 14.32
安雅 9.81 37.48 汪惟 10.26 64.13 周晓农 8.97 47.54
王路 22.39 38.22 pansz 13.04 34.85 涛吴 10.29 37.20
梁边妖 10.26 79.40 Lightwing 3.68 31.17 谭蔓茹 2.61 13.39
倪一宁 3.76 51.21 带三个表 9.27 19.16 Lydia 2.63 89.12
李淼 21.23 39.31 沃金 2.79 29.81 李开复 31.16 13.02
极乐 10.12 45.18 李楠 23.13 16.28 夏昊BFA 35.45 62.92
蒋校长 8.92 1.13 张亮 72.12 70.08
回归系数 t值 p值
知识能力指数 0.8020 3.090 0.00278
传播影响力指数 1.2039 7.106 5.22e-10
answer 0.002676 1.002 0.31996
question 0.05065 2.654 0.00984
article 0.03714 1.567 0.12166
agree 0.00003078 1.808 0.07494
topic -0.05145 -1.257 0.21310
betweeness 0.01136 0.056 0.95585
degree.out 1.521 1.888 0.06313
degree.in -0.6753 -0.981 0.33001
degree.total 1.1364 0.616 0.54021
shole 1.088 1.149 0.25456
[1] 韦勇娇. 认知盈余时代, 网络问答社区的知识传播模式探析——以“知乎”为例[J]. 广西职业技术学院学报, 2014, 7(1): 30-34, 40.
[1] (Wei Yongjiao.Analysis of Modes of Knowledge Dissemination Online Q&A——A Case Study of Zhihu Q&A Website[J]. Journal of Guangxi Vocational and Technical College, 2014, 7(1): 30-34, 40.)
[2] 吕峰. 基于隐马尔科夫模型的问答社区用户知识贡献意愿研究[D]. 哈尔滨: 哈尔滨工业大学, 2015.
[2] (Lv Feng.Research on the Knowledge Contribution Intention in Q&A Community Based on Hidden Markov Model[D]. Harbin: Harbin Institute of Technology, 2015.)
[3] 金家华. 社会化问答社区中用户知识行为的影响因素研究[D]. 哈尔滨: 哈尔滨工业大学, 2015.
[3] (Jin Jiahua.Research on the Influence Factors of User’s Knowledge Activities in Online Social Q&A Community[D]. Harbin:Harbin Institute of Technology, 2015.)
[4] 陈娟, 高杉, 邓胜利. 社会化问答用户特征识别与行为动机分析——以“知乎”为例[J]. 情报科学, 2017, 35(5): 69-74, 80.
[4] (Chen Juan, Gao Shan, Deng Shengli.Characteristics Recognition and Motivation Analysis of Social Q&A Users——A Case Study of ‘Zhihu’ Website[J]. Information Science, 2017, 35(5): 69-74, 80.)
[5] 黄梦婷, 张鹏翼. 社会化问答社区的协作方式与效果研究: 以知乎为例[J]. 图书情报工作, 2015, 59(12): 85-92.
doi: 10.13266/j.issn.0252-3116.2015.12.013
[5] (Huang Mengting, Zhang Pengyi.Collaboration Forms and Effectiveness in Social Q&A Communities: A Case Study of Zhihu.com[J]. Library and Information Service, 2015, 59(12): 85-92.)
doi: 10.13266/j.issn.0252-3116.2015.12.013
[6] 刘佩, 林如鹏. 网络问答社区“知乎”的知识分享与传播行为研究[J]. 图书情报知识, 2015(6): 109-119.
doi: 10.13366/j.dik.2015.06.109
[6] (Liu Pei, Lin Rupeng.Research on Knowledge Sharing and Dissemination Behavior of Online Q&A Services: Taking Zhihu as an Example[J]. Documentation, Information & Knowledge, 2015(6): 109-119.)
doi: 10.13366/j.dik.2015.06.109
[7] Liu Z, Jansen B J.Questioner or Question: Predicting the Response Rate in Social Question and Answering on Sina Weibo[J]. Information Processing & Management, 2018, 54(2): 159-174.
doi: 10.1016/j.ipm.2017.10.004
[8] Jin J, Li Y, Zhong X, et al.Why Users Contribute Knowledge to Online Communities: An Empirical Study of an Online Social Q&A Community[J]. Information & Management, 2015, 52(7): 840-849.
doi: 10.1016/j.im.2015.07.005
[9] Lou J, Fang Y, Lim K H, et al.Contributing High Quantity and Quality Knowledge to Online Q&A Communities[J]. Journal of the Association for Information Science and Technology, 2013, 64(2): 356-371.
[10] 左遥, 梁英, 毕晓迪, 等. 社会化问答网站知识传播网络推断方法[J]. 计算机学报, 2018, 41(1): 82-97.
[10] (Zuo Yao, Liang Ying, Bi Xiaodi, et al.An Inference Method of Knowledge Diffusion Network in Community Question Answering Sites[J]. Chinese Journal of Computers, 2018, 41(1): 82-97.)
[11] 宁菁菁. 基于“弱关系理论”的知识问答社区知识传播研究——以知乎网为例[J]. 新闻知识, 2014(2): 98-99,50.
doi: 10.3969/j.issn.1003-3629.2014.02.038
[11] (Ning Jingjing.Research on Knowledge Communication in Knowledge Q&A Community Based on “Weak Relationship Theory”—— A Case Study of Zhihu Network[J]. News Research, 2014(2): 98-99, 50.)
doi: 10.3969/j.issn.1003-3629.2014.02.038
[12] Cowan R, Jonard N.Network Structure and the Diffusion of Knowledge[J]. Journal of Economics Dynamics and Control, 2004, 28(8): 1557-1575
doi: 10.1016/j.jedc.2003.04.002
[13] Matlab [K/OL]. [2018-04-13].https://www.mathworks.com/.
[14] 王嘉. 思想政治教育视域下的网络意见领袖研究[D]. 大连: 大连理工大学, 2013.
[14] (Wang Jia.Researches on Network Opinion Leader for Ideological and Political Education [D]. Dalian: Dalian University of Technology, 2013.)
[15] 赵基明, 邱均平, 黄凯, 等. 一种新的科学计量指标——h指数及其应用述评[J]. 中国科学基金, 2008(1): 23-32.
doi: 10.3969/j.issn.1000-8217.2008.01.005
[15] (Zhao Jiming, Qiu Junping, Huang Kai, et al.A New Scientometric Indicator——Review on h Index and Its Application[J]. Bulletin of National Natural Science Foundation of China, 2008(1): 23-32.)
doi: 10.3969/j.issn.1000-8217.2008.01.005
[16] Rstudio [K/OL]. [2018-04-13]..
[17] 汪小帆, 李翔, 陈关荣. 网络科学导论[M]. 北京: 高等教育出版社, 2012: 233.
[17] (Wang Xiaofan, Li Xiang, Chen Guanrong.Network Science: An Introduction[M]. Beijing: Higher Education Press, 2012: 233.)
[18] Tan P-N, Steinbach M, Kumar V.数据挖掘导论(完整版) [M]. 范明, 范宏建等译. 北京: 人民邮电出版社, 2011: 38-39.
[18] (Tan P-N, Steinbach M, Kumar V.Introdution to Data Mining[M]. Translated by Fan Ming, Fan Hongjian, et al. Beijing: Post & Telecom Press, 2011: 38-39.)
[19] 张继国, 辛格. 信息熵——理论与应用[M]. 北京: 中国水利水电出版社, 2012:1-2.
[19] (Zhang Jiguo, Singh V P.Information Entropy——Theory and Application[M]. Beijing: China Water & Power Press, 2012: 1-2.)
[20] 芦白茹, 张坤严, 心娥, 等. 基于AHP法和熵权法组合权重对RC结构危险房屋多层次模糊综合评定研究[C]. 见: 第25届全国结构工程学术会议论文集, 2016: 89.
[20] (Lu Bairu, Zhang Kuyan, Xin E, et al.Multi-hierarchy Fuzzy Comprehensive Assessment of RC Structure Dangerous Buildings Based on Combined Weights of AHP and Entropy-weighted Method[C]// Proceedings of the 25th National Conference on Structural Engineering. 2016: 89.)
[21] Shannon C E.A Mathematical Theory of Communication[J]. Bell System Technical Journal, 1948, 27(3): 379-423.
doi: 10.1002/j.1538-7305.1948.tb01338.x
[22] Kermack W O, McKendrick A G. Contributions to the Mathematical Theory of Epidemics. II.—The Problem of Endemicity[J]. Proceedings of the Royal Society of London A, 1932, 138(834): 55-83.
doi: 10.1098/rspa.1932.0171
[23] 李中师. 基于个体差异的复杂网络下隐性知识传播模型研究[D]. 杭州: 浙江工业大学, 2012.
[23] (Li Zhongshi.Study of Tacit Knowledge Transfer Based on Individual Differences in Complex Social Networks[D]. Hangzhou: Zhejiang University of Technology, 2012.)
[24] 张红兵. 虚拟企业知识转移的研究[M]. 北京: 经济管理出版社, 2009: 56.
[24] (Zhang Hongbing.Research on the Knowledge Transfer in Virtual Enterprise[M]. Beijing: Economics & Management Publishing House, 2009: 56.)
[25] 汪应洛. 系统工程[M]. 第4版. 北京: 机械工业出版社, 2008: 82.
[25] (Wang Yingluo. System Engineering[M]. The 4th Edition. Beijing: China Machine Press, 2008: 82.)
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[9] Wang Yuefen,Jin Jialin. Characteristics and Development Trends of Papers from “New Technology of Library and Information Service”[J]. 现代图书情报技术, 2016, 32(9): 1-16.
[10] Wu Huijuan,Jia Tina Du,Sun Hongfei,Jannatul Fardous. Identifying Core Users in Social Resource Recommendation System with K-shell Collapse Sequences[J]. 现代图书情报技术, 2016, 32(9): 58-64.
[11] Ye Teng,Han Lichuan,Xing Chunxiao,Zhang Yan. Knowledge Dissemination Mechanism in Virtual Communities: Case Study Based on Complex Network Theory[J]. 现代图书情报技术, 2016, 32(7-8): 70-77.
[12] Wu Yingliang, Yao Huaidong, Li Cheng'an. An Improved Collaborative Filtering Recommendation Algorithm with Indirect Trust Relationship[J]. 现代图书情报技术, 2015, 31(9): 38-45.
[13] Ren Ni, Zhou Jiannong. The Discovery and Evaluation of Research Team Under the Mode of Weighted Co-Author Network[J]. 现代图书情报技术, 2015, 31(9): 68-75.
[14] Zhai Shanshan, Xu Xin, Xia Lixin. A Review of User Communication and Knowledge Dissemination in Academic Blogs[J]. 现代图书情报技术, 2015, 31(7-8): 3-12.
[15] Tan Min, Xu Xin. The Empirical Study of h-Degree in Recommendation Network of Academic Blogs——Taking ScienceNet.cn Blogs as an Example[J]. 现代图书情报技术, 2015, 31(7-8): 31-36.
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