社交网络意见领袖“同心圈层”：现象、结构及规律

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Abstract The opinion leaders in social networks are not polycentric or diversified, but have created a convergent structure of “concentric circles”. Taking the influence of the opinion leaders as an independent variable, we find that with their increasing influence the opinion leaders create a convergent structure of “concentric circles” with one center, three convergence supports and gradual convergent circles. The opinion leaders are “social models” in the center of the convergent structure. Their influence is positively related to how much they are convergent with the “social models” in the center. In this process, concentric circles are formed around the center. The closer to the center, the denser the circles, and vice versa. Taking Sina Weibo, one of the typical social networks, as a sample, we tested our hypotheses. The research bears out our conception of the “concentric circles”. First, the influence of the opinion leader is positively correlated with his distance from the “social model” in the center, and thus the opinion leader is ready to get closer to the network center. Second, in the process of users converging to the central social model, there is a positive correlation and isomorphism between the influence of the opinion leader and influence of the “social model”. Third, the extent to which a network user is taken as a social model is positively related to how much his opinion is similar to the social model in the center, showing that the “social model” is located only in the center, and that it is homogeneous rather than diverse. Fourth, with their opinion leader moving to a higher level, the users get more convergent within their hierarchy, and thus the user influence gets more coherent and narrower. The convergence and the “concentric circles” of the opinion leader users show that the decentralized network era is re-centralized, and a “one-dimensional” society is coming into being in the “Balkanization” era of network.

Key words： social network users key opinion leaders concentric circles user convergence content similarity recentralization “one-dimensional” society;

Received: 10 September 2021

PACS:	G20
	G206.2

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	XU Xiang

Cite this article:

XU Xiang. “Concentric Circles” of Opinion Leaders in Social Networks: Phenomenon, Structure and Law[J]. , 2022, 39(1): 133-148.

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https://xb.szu.edu.cn/EN/ OR https://xb.szu.edu.cn/EN/Y2022/V39/I1/133

[1] (美)克莱·舍基.人人时代[M].胡泳,沈满琳译.杭州:浙江人民出版社,2015.29-36.
[2] (美)马克·波斯特.第二媒介时代[M].范静哗译.南京:南京大学出版社,2001.22-28.
[3] 胡泳. 众声喧哗——网络时代的个人表达与公共讨论[M].桂林:广西师范大学出版社,2008.123-232.
[4] Jenkins H,Purushotma R,Weigel M,et al.Confronting the challenges of participatory culture[J].Educational Geront-ology,2009,29(7):617-626.
[5] 曹洵,张志安.基于媒介权力结构的微博意见领袖影响力研究[J].新闻界,2016,(9):43-49.
[6] 佟力强. 中国微博发展报告(2012)[M].北京:人民出版社,2013.27-28.
[7] 张玉晨,翟姗姗,许鑫等.微博“中V”用户的传播特征及其引导力研究[J].图书情报工作,2018,62(11).
[8] 陈福平,许丹红.观点与链接:在线社交网络中的群体政治极化[J].社会,2017,37(4):217-240.
[9] Marshall V Alstyne,Erik Brynjolfsson.Global village or cyber-balkans?modeling and measuring the integration of electronic communities[J].Management Science,2005,51(6):851-868.
[10] 生奇志,高森宇.中国微博意见领袖:特征、类型与发展趋势[J].东北大学学报(社会科学版),2013,(4):381-385.
[11] 王晗啸,于德山.意见领袖关系及主题参与倾向研究——基于微博热点事件的耦合分析[J].新闻与传播研究,2018, 25(1):51-65+127.
[12] 王国华,张剑,毕帅辉.突发事件网络舆情演变中意见领袖研究——以药家鑫事件为例[J].情报杂志,2011,(12):1-5.
[13] 刘果. 微博意见领袖的角色分析与引导策略[J].武汉大学学报(人文科学版),2014,67(2):115-118.
[14] 王国华,张勇波,王雅蕾,刘炼.微博意见领袖的类型特征与内容指向研究[J].电子政务,2014,(8).
[15] 任纪舜等. 中国东部及邻区大陆岩石圈的构造演化与成矿[M].北京:科学出版社,1990.1-21.
[16] (德)约翰·冯·杜能.孤立国同农业和国民经济的关系[M].吴衡康译.北京:商务印书馆,1997.88-90.
[17] (美)罗伯特·帕克,欧内斯特·伯吉斯.城市社会学——芝加哥学派城市研究[M].宋俊岭,郑也夫译.北京:商务印书馆,2012.50-53 .
[18] Myrdal G.Economic Theory and Under-developed Regions[M].London:Duckworth,1957.28-58.
[19] Matsumura N, Ohsawa Y, Ishizuka M.Influence Diffusion Model in Text Based Communication[J].Transactions of the Japanese Society for Artificial Intelligence,2002,17(3):259-267.
[20] Borge Bravo R,Marc E D V.Opinion leadership in parliamentary Twitter networks:A matter of layers of interaction?[J].Journal of Information Technology&Politics,2017, 14(3):1-14.
[21] 王晓光. 博客社区内的非正式交流:基于网络链接的实证分析[J].情报学报,2009,(2):248-256.
[22] Weng J,Lim E P,Jiang J,et al. TwitterRank:Finding Topic-Sensitive Influential Twitterers[EB/OL].http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.649.884&rep=rep1&type=pdf, 2021-09-25.
[23] 李根强,方从慧.复杂网络视角下网络集群行为主体的观点演化研究[J].情报科学,2017,35(5):125-131.
[24] 李卫东,彭静.社交网络平台信息传播的回声室效应仿真实验分析[J].现代传播(中国传媒大学学报),2019,41(4):142-149.
[25] Yoo E,Gu B,Rabinovich E.Diffusion on social media platforms:A point process model for interaction among similar content[J].Journal of Management Information Sy-stems,2019,36(4):1105-1141.
[26] Mikal J P,Rice R E,Kent R G,et al.Common voice: Analysis of behavior modification and content convergence in a popular online community[J].Computers in Human Behavior,2014,35(35):506-515.
[27] Lee R K W,Hoang T A,Lim E P.On analyzing user topicspecific platform preferences across multiple social media sites[EB/OL].https://www.researchgate.net/profile/Roy-Ka-Wei-Lee-2/publication/316238570_On_Analyzing_User_Topic-Specific_Platform_Preferences_Acro ss_Mu liple_Social_Media_Sites/links/58f6edb80f7e9b67a34ba5 44/On-Analyzing-User-Topic-Specific-Platform-Preferences-Across-Multiple-Social-Media-Sites.pdf,2021-10-24.
[28] Masson A R, Hayel Y, Altman E.Posting behavior dynamics and active filtering for content diversity in social networks[J].IEEE Transactions on Signal and Information Processing over Networks,2017,3(2):376-387.
[29] 翟秀凤. 创意劳动抑或算法规训?——探析智能化传播对网络内容生产者的影响[J].新闻记者,2019,(10):4-11.
[30] Litt E, Hargittai E.The imagined audience on social network sites[J].Social Media &Society,2016,2(1):1-12.
[31] Saridou T, Spyridou L P, Veglis A.Churnalism on the rise? Assessing convergence effects on editorial practices[J].Digital Journalism,2017,5(8):1006-1024.
[32] 曹洵,张志安.社交媒体意见群体的特征、变化和影响力研究[J].新闻界,2017,(7):28-34.
[33] (美)布雷恩·S·布鲁克斯等.新闻报道与写作[M].范红译.北京:新华出版社,2007.48-50.
[34] 王国华,郑全海,王雅蕾,熊伟强,谢宏. 新浪热门微博的特征及用户转发规律研究[J].情报杂志,2014,33(4):117-121+89.
[35] 陈昌凤. 同质化的信息消费:2013年我们在关注什么——中国四地2013年谷歌搜索热点数据分析[J].新闻与写作,2014,31(2):50-52.
[36] 韦路,胡雨濛.中国微博空间的议题呈现: 新浪热门微博实证研究[J].浙江大学学报(人文社会科学版),2014, 44(2):41-52.
[37] 蔡卫平. 传媒同质化现象动因探析[J].当代传播(汉文版),2008,(3):34-36.
[38] 王君泽,王雅蕾,禹航等.微博客意见领袖识别模型研究[J].新闻与传播研究,2011,18(6):81-88+111.
[39] 刘志明,刘鲁.微博网络舆情中的意见领袖识别及分析[J].系统工程,2011,(6):8-16.
[40] 新浪微博数据中心. 2018微博用户发展报告[EB/OL].https://data.weibo.com/report/reportDetail?id=433,2019-03-15.
[41] Dumais S T.Latent semantic analysis[J].Annual review of information science and technology,2004,(1):188-230.
[42] 易丹辉. 结构方程模型:方法与应用[M].北京:中国人民大学出版社,2008.127.
[43] 李保东. 结构方程模型在组织认同研究中的应用[M].北京:经济管理出版社,2014.84-85.
[44] (德)马克斯·霍克海默,(德)西奥多·阿道尔诺.启蒙辩证法——哲学断片[M].渠敬东,曹卫东译.上海:世纪出版集团,上海人民出版社,2006.107-152.
[45] (美)赫伯特·马尔库塞.单向度的人[M].刘继译.上海:世纪出版集团,上海人民出版社,2008.1-96.