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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (11): 54-63    DOI: 10.11925/infotech.2096-3467.2018.0320
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Detecting Relationship Among WeChat Group Members with Co-occurrence of Cooperation
Li Gang1, Wang Xiao1(), Guo Yang2
1Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China
2School of Information Management, Central China Normal University, Wuhan 430079, China
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Abstract  

[Objective] This paper analyzes the implicit relationship among WeChat group members and meaures its strength, which is also combined with their explicit relatinship to describe the social network characteristics of WeChat groups. [Methods] First, we collected chatting records from one WeChat interest group. Then, we used the co-occurrence to measure the implicit relationship and the salton index to calculate their strength. Third, we analyzed the discussion participation to explore the implicit-relationship distribution. Finally, we compared the full-relationship network with explicit-relationship network. [Results] We found that topic discussion clearly reflected relationship among group members. Posting more relevant topics helps to manage and maintain membership. [Limitations] More research is needed to measure goup members’ engagement. [Conclusions] The full-network with implicit and explicit relationship reveals more insights on the structure of WeChat group.

Key wordsWeChat Group      Social Network      User Relations     
Received: 23 March 2018      Published: 11 December 2018
ZTFLH:  G203  

Cite this article:

Li Gang,Wang Xiao,Guo Yang. Detecting Relationship Among WeChat Group Members with Co-occurrence of Cooperation. Data Analysis and Knowledge Discovery, 2018, 2(11): 54-63.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0320     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I11/54

[1] 腾讯. 腾讯公布2017年第三季度业绩[R/OL]. (2017-11-15). 2018-02-24].
[1] (Tencent. Tencent Announces the Third Quarter Report of 2017 Performance [R/OL]. (2017-11-15). [2018-02-24]. .)
[2] 微博数据中心. 2017微博用户发展报告[R/OL]. (2017-12-25). [2018-02-24]. .
[2] (Weibo Data Center. 2017 Report of Weibo User Development [R/OL]. (2017-12-25). [2018-02-24].
[3] 腾讯研究. 2016微信经济社会影响力研究报告[R/OL]. (2017-04-17). [2017-06-08]. .
[3] (Tencent Research Institute. 2016 WeChat Social and Economic Impact Study Report[R/OL]. (2017-04-17). [2017-06-08].
[4] 王芳, 翟羽佳. 微信群社会结构及其演化: 基于文本挖掘的案例分析[J]. 情报学报, 2016, 35(6): 617-629.
doi: 10.3772/j.issn.1000-0135.2016.006.006
[4] (Wang Fang, Zhai Yujia.Social Structure and Evolvement of Wechat Groups: A Case Study Based on Text Mining[J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(6): 617-629.)
doi: 10.3772/j.issn.1000-0135.2016.006.006
[5] 禹卫华. 微信群的传播分析: 节点、文本与社交网络——以三个校园微信群为例[J]. 新闻记者, 2016(10): 61-65.
[5] (Yu Weihua.Analysis of WeChat Group Communication: Nodes, Texts, and Social Networks: A Case Study of Three Campus WeChat Groups[J]. Shanghai Journalism Review, 2016(10): 61-65.)
[6] 李蕴秀. 校园微信社群的关系嵌入研究[D]. 广州: 暨南大学, 2016.
[6] (Li Yunxiu.Investigation for Relational Embeddedness of the Campus WeChat Virtual Community [D]. Guangzhou: Jinan University, 2016.)
[7] 罗自文. 网络趣缘群体的基本特征与传播模式研究——基于6个典型网络趣缘群体的实证分析[J]. 新闻与传播研究, 2013(4): 101-111.
[7] (Luo Ziwen.Research on the Basic Characteristics and Communication Model of Interest-related Group: An Empirical Analysis Based on Six Typical Internet Interest-related Group[J]. Journalism & Communication, 2013(4): 101-111.)
[8] Granovetter M S.The Strength of Weak Ties[J]. American Journal of Sociology, 1973, 78(6): 1360-1380.
doi: 10.1086/225469
[9] Granovetter M S.The Strength of Weak Ties: A Network Theory Revisited[J]. Sociological Theory, 1983, 1(6): 201-233.
doi: 10.2307/202051
[10] Friedkin N E.Information Flow Through Strong and Weak Ties in Intra-organizational Social Networks[J]. Social Networks, 1982, 3(4): 273-285.
doi: 10.1016/0378-8733(82)90003-X
[11] Weimann G.The Strength of Weak Conversational Ties in the Flow of Information and Influence[J]. Social Networks, 1983, 5(3): 245-267.
doi: 10.1016/0378-8733(83)90027-8
[12] Centola D, Macy M.Complex Contagions and the Weakness of Long Ties[J]. American Journal of Sociology, 2007, 113(3): 702-734.
doi: 10.1086/521848
[13] Kavanaugh A L, Reese D D, Carroll J M, et al.Weak Ties in Networked Communities[J]. The Information Society, 2005, 21(2): 119-131.
doi: 10.1080/01972240590925320
[14] Barrat A, Barthélemy M, Pastor-Satorras R, et al.The Architecture of Complex Weighted Networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(11): 3747-3752.
doi: 10.1073/pnas.0400087101
[15] 俞琰, 邱广华, 李珊. 社交网站交互模式分析[J]. 情报学报, 2012, 31(2): 213-224.
doi: 10.3772/j.issn.1000-0135.2012.02.013
[15] (Yu Yan, Qiu Guanghua, Li Shan.Analysis of Interaction Pattern in Social Networking Sites[J]. Journal of the China Society for Scientific and Technical Information, 2012, 31(2): 213-224.)
doi: 10.3772/j.issn.1000-0135.2012.02.013
[16] 石彭辉. 基于社会网络分析的网络舆情实证研究[J]. 现代情报, 2013, 33(2): 27-31.
doi: 10.3969/j.issn.1008-0821.2013.02.007
[16] (Shi Penghui.Empirical Studies of Network Public Opinion Based on Social Network Analysis[J]. Journal of Modern Information, 2013, 33(2): 27-31.)
doi: 10.3969/j.issn.1008-0821.2013.02.007
[17] Wellman B, Wortley S.Different Strokes from Different Folks: Community Ties and Social Support[J]. American Journal of Sociology, 1990,96(3): 558-589.
doi: 10.1086/229572
[18] Lin N.Social Network and Status Attainment[J]. Annual Review of Sociology, 1999, 25: 467-487.
doi: 10.1146/annurev.soc.25.1.467
[19] Zhang Y, Yu T.Mining Trust Relationships from Online Social Networks[J]. Journal of Computer Science and Technology, 2012, 27(3): 492-505.
doi: 10.1007/s11390-012-1238-8
[20] Fogués R L, Such J M, Espinosa A, et al.BFF: A Tool for Eliciting Tie Strength and User Communities in Social Networking Services[J]. Information Systems Frontiers, 2014, 16(2): 225-237.
doi: 10.1007/s10796-013-9453-6
[21] Singla P, Richardson M.Yes, There is a Correlation: From Social Networks to Personal Behavior on the Web[C]// Proceedings of the 17th International Conference on World Wide Web. New York, USA: ACM, 2008: 655-664.
[22] 杨媛媛. SNS网络中节点关系研究[D]. 保定: 河北农业大学, 2010.
[22] (Yang Yuanyuan.Research of Nodes Relationships in SNS Networks[D]. Baoding: Agricultural University of Hebei, 2010.)
[23] Horowitz D, Kamvar S D.The Anatomy of a Large-scale Social Search Engine[C]// Proceedings of the 19th International Conference on World Wide Web, Raleigh, North Carolina, USA. New York, USA: ACM, 2010: 431-440.
[24] Choudhury M D, Mason W A, Hofman J M, et al.Inferring Relevant Social Networks from Interpersonal Communication[C]//Proceedings of the 19th International Conference on World Wide Web, Raleigh, North Carolina, USA. New York, USA: ACM, 2010: 301-310.
[25] Onnela J P, Saramäki J, Hyvönen J, et al.Structure and Tie Strengths in Mobile Communication Networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2007, 104(18): 7332-7336.
doi: 10.1073/pnas.0610245104 pmid: 17456605
[26] 于岩,陈鸿昶,于洪涛. 基于霍克斯过程的社交网络用户关系强度模型[J]. 电子学报, 2016, 44(6): 1362-1368.
doi: 10.3969/j.issn.0372-2112.2016.06.015
[26] (Yu Yan, Chen Hongchang, Yu Hongtao.A Social Networks User Relationship Strength Model Based on Hawkes Process[J]. Acta Electronica Sinica, 2016, 44(6): 1362-1368.)
doi: 10.3969/j.issn.0372-2112.2016.06.015
[27] 韩忠明, 谭旭升, 陈炎,等. 基于隐回归的用户关系强度模型[J]. 计算机应用, 2016, 36(2): 336-341.
doi: 10.11772/j.issn.1001-9081.2016.02.0336
[27] (Han Zhongming, Tan Xusheng, Chen Yan, et al.Strength Model of User Relationship Based on Latent Regression[J]. Journal of Computer Applications, 2016, 36(2): 336-341.)
doi: 10.11772/j.issn.1001-9081.2016.02.0336
[28] Taboada M, Wiesemann L.Subjects and Topics in Conversation[J]. Journal of Pragmatics, 2010, 42(7): 1816-1828.
doi: 10.1016/j.pragma.2009.04.009
[29] Maynard D W.Placement of Topic Changes in Conversation[J]. Semiotica, 1980, 30(3-4): 263-290.
[30] 孙国军. 论会话话题[J]. 外语研究, 1993(1): 37-41, 50.
[30] (Sun Guojun.On Conversational Topics[J]. Foreign Language Research, 1993(1): 37-41, 50.)
[31] 丰国欣. 话轮转换与话题转换[J]. 湖北师范学院学报: 哲学社会科学版, 2000, 20(4): 41-44.
[31] (Feng Guoxin.Turn-taking and Topic Change[J]. Journal of Hubei Normal University: Philosophy and Social Science, 2000, 20(4): 41-44.)
[32] Geluykens R.Topic Introduction in English Conversation[J]. Transactions of the Philological Society, 1993, 91(2): 181-214.
doi: 10.1111/j.1467-968X.1993.tb01068.x
[33] 蒋永福, 李集. 信息运动十大规律[J]. 情报资料工作, 1998(5): 18-21.
[33] (Jiang Yongfu, Li Ji.Ten Laws of Information Movement[J]. Information and Documentation Services, 1998(5): 18-21.)
[34] Sansonnet J P.Conversational Topics Handle Social Relationships[C]//Proceedings of the 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction. Washington DC, USA: IEEE Computer Society, 2013: 203-208.
[35] 张超星, 刘小玲, 谭宗颖. 图情领域的大共现及其发展现状[J]. 情报资料工作, 2016(1): 29-35.
[35] (Zhang Chaoxing, Liu Xiaoling, Tan Zongying.The Big Co-occurrence and Its Development Status in Library and Information Field[J]. Information and Documentation Service, 2016(1): 29-35.)
[36] 邱均平,董克. 作者共现网络的科学研究结构揭示能力比较研究[J]. 中国图书馆学报, 2014, 40(1): 15-24.
doi: 10.3969/j.issn.1001-8867.2014.01.002
[36] (Qiu Junping, Dong Ke.A Comparative Study on the Ability of Author Co-occurrence Network in Revealing Scientific Structure[J]. Journal of Library Science in China, 2014, 40(1): 15-24.)
doi: 10.3969/j.issn.1001-8867.2014.01.002
[37] 许海云, 方曙. 科学计量学的研究主题与发展——基于普赖斯奖得主的扩展作者共现分析[J]. 情报学报, 2013, 32(1): 58-67.
doi: 10.3772/j.issn.1000-0135.2013.01.007
[37] (Xu Haiyun, Fang Shu.Research Topics and Development of Scientometrics: Based on Co-occurrence Analysis of Price Award Winner[J]. Journal of the China Society for Scientific and Technical Information, 2013, 32(1): 58-67.)
doi: 10.3772/j.issn.1000-0135.2013.01.007
[38] Golbeck J.Trust and Nuanced Profile Similarity in Online Social Networks[J]. ACM Transactions on the Web, 2009, 3(4): Article No.12.
doi: 10.1145/1594173.1594174
[39] 谢玉进. 网络趣缘群体与青少年发展[J]. 中国青年研究, 2006(7): 60-63.
doi: 10.3969/j.issn.1002-9931.2006.07.016
[39] (Xie Yujin.Internet Interest-related Group and Youth Development[J]. China Youth Study, 2006(7): 60-63.)
doi: 10.3969/j.issn.1002-9931.2006.07.016
[40] 黄继新. 任何以外部特征作为归类来划分的群体及社交关系, 本质上都是虚假的[EB/OL].(2015-12-15).[2017-06-05]. .
[40] (Huang Jixin. Any Group and Social Relationship Divided by External Features as a Category are Inherently False[EB/OL]. (2015-12-15). [2017-06-05].
[41] 王巍. 会话话题分析——话题在会话结构中的运行规则考察[D]. 长春: 吉林大学, 2006.
[41] (Wang Wei.Analysis of Discourse Topic——On the Running Rules of Discourse Topic in Conversational Structure[D]. Changchun: Jilin University, 2006. )
[42] 潘玉雯. 关于话题间关系问题的研究[J]. 西昌学院学报: 社会科学版, 2008, 20(3): 15-17, 31.
doi: 10.3969/j.issn.1673-1883.2008.03.003
[42] (Pan Yuwen.On the Relationships Between Topics[J]. Journal of Xichang College: Social Science Edition, 2008, 20(3): 15-17, 31.)
doi: 10.3969/j.issn.1673-1883.2008.03.003
[43] 隆连堂, 姜照华, 刘则渊, 等. 中国区域知识生产合作强度的定量分析[J]. 科技进步与对策, 2006, 23(1):62-64.
doi: 10.3969/j.issn.1001-7348.2006.01.017
[43] (Long Liantang, Jiang Zhaohua, Liu Zeyuan, et al.Quantitative Analysis of Regional Knowledge Production Cooperation in China[J]. Science & Technology Progress and Policy, 2006, 23(1): 62-64.)
doi: 10.3969/j.issn.1001-7348.2006.01.017
[44] Savanur K, Srikanth R.Modified Collaborative Coefficient: A New Measure for Quantifying the Degree of Research Collaboration[J]. Scientometrics, 2010, 84(2): 365-371.
doi: 10.1007/s11192-009-0100-4
[45] Liao C H, Yen H R.Quantifying the Degree of Research Collaboration: A Comparative Study of Collaborative Measures[J]. Journal of Informetrics, 2012, 6(1): 27-33.
doi: 10.1016/j.joi.2011.09.003
[46] Luukkonen T, Tijssen R J W, Persson O, et al. The Measurement of International Scientific Collaboration[J]. Scientometrics, 1993, 28(1): 15-36.
doi: 10.1007/BF02016282
[47] 雷茵. 社交网络人物关系强度估算方法研究[D]. 南昌: 华东交通大学, 2016.
[47] (Lei Yin.Research on the Estimation Method of Social Network Relationship Strength[D]. Nanchang: East China Jiaotong University, 2016.)
[48] 梁立明,沙德春. 985高校校际科学合作的强地域倾向[J]. 科学学与科学技术管理, 2008, 29(11): 112-116.
[48] (Liang Liming, Sha Dechun.Strong Geographical Preferences in Scientific Collaboration Between “985 Project” Universities[J]. Science of Science and Management of S.& T., 2008, 29(11): 112-116.)
[49] 王双, 陈毓芬, 袁烨城, 等. 科学合作地域倾向性研究_以中国雾霾研究为例[J]. 地球信息科学学报, 2017, 19(2): 248-255.
[49] (Wang Shuang, Chen Yufen, Yuan Yecheng, et al.Research on Geographical Preference of Scientific Collaboration: A Case Study of Haze Research Network in China[J]. Journal of Geo-information Science, 2017, 19(2): 248-255.)
[50] 苏金燕. 我国人文社会科学合作的地域倾向研究——基于经济学期刊论文的计量分析[J]. 现代图书情报技术, 2013(10): 43-52.
[50] (Su Jinyan.Regional Tendencies of Research Collaboration of Social Sciences in China —— Analysis Based on Papers of Economic Journals[J]. New Technology of Library and Information Service, 2013(10): 43-52.)
[51] Haustein S, Baelz G, Baelz G, et al.Reasons for and Developments in International Scientific Collaboration: Does An Asia-Pacific Research Area Exist from a Bibliometric Point of View?[J]. Scientometrics, 2011, 86(3): 727-746.
doi: 10.1007/s11192-010-0295-4
[52] Hoekman J, Frenken K, Oort F V.The Geography of Collaborative Knowledge Production in Europe[J]. Kites Working Papers, 2009, 43(3): 721-738.
doi: 10.1007/s00168-008-0252-9
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