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数据分析与知识发现  2016, Vol. 32 Issue (12): 85-93     https://doi.org/10.11925/infotech.1003-3513.2016.12.11
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社交媒体舆情信息传播效果影响因素研究*——以新浪微博“8.12天津爆炸”事件为例
廖海涵,王曰芬()
南京理工大学经济管理学院 南京 210094
Public Opinion Dissemination over Social Media: Case Study of Sina Weibo and “8.12 Tianjin Explosion”
Haihan Liao,Yuefen Wang()
School of Economics and Management, Nanjing University of Science & Technology, Nanjing 210094, China
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摘要 

目的】研究社交媒体舆情信息传播规律和信息传播效果影响因素, 为政府管理实践和相关决策提供参考依据。【方法】结合5W传播模式和议程设置理论对信息传播因素提出假设, 采用相关性分析进行验证。【结果】研究发现传播群体中意见领袖群体对传播效果影响最大, 微博发布者属性与传播效果存在正相关关系, 信息传播数量与传播效果成负相关关系。【局限】由于受到时间、技术等限制, 只选择单一话题在单一时间内的传播情况做了实证分析。【结论】对政府机构、新闻媒体、大型企业等管理者了解舆情传播影响情况及舆情信息影响因素探索研究具有重要意义。

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王曰芬
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关键词 信息传播社交媒体影响因素假设验证    
Abstract

[Objective]This paper studies the dissemination of public opinion over the social media, with the purpose of improving government management and decision making. [Methods] We set hypothesises of information dissemination with the 5W communication model and agenda setting theory, and then conducted correlation analysis to data from Sina Weibo. [Results] We found that the opinion leaders posed more impacts to the communication results. There was positive correlation between the attributes of micro-blog posters and communication results, while the correlation between volumes of disseminated information and the results was negative. [Limitations] We only chose one single topic from a specific period of time to conduct the empirical analysis. [Conclusions] This study could help the government, news agencies, and large enterprises understand the impacts and influencing factors of public opinions dissemination.

Key wordsInformation dissemination    Social media    Influencing factor    Hypothesis verification
收稿日期: 2016-06-12      出版日期: 2017-01-22
基金资助:*本文系国家社会科学基金重点项目“大数据环境下社会舆情与决策支持方法体系研究”(项目编号: 14AZD084)和江苏高校哲学社会科学重点研究基地“社会计算与舆情分析”(培育点)的研究成果之一
引用本文:   
廖海涵, 王曰芬. 社交媒体舆情信息传播效果影响因素研究*——以新浪微博“8.12天津爆炸”事件为例[J]. 数据分析与知识发现, 2016, 32(12): 85-93.
Haihan Liao, Yuefen Wang. Public Opinion Dissemination over Social Media: Case Study of Sina Weibo and “8.12 Tianjin Explosion”. Data Analysis and Knowledge Discovery, 2016, 32(12): 85-93.
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https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2016.12.11      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2016/V32/I12/85
[1] CNNIC. 第37次中国互联网络发展状况统计报告[R/OL]. [2016-04-07]. .
[1] (The 37th Statistical Report on the Development of the Internet in China[R/OL]. [2016- 04-07].
[2] 李纲, 陈璟浩. 突发公共事件网络舆情研究综述[J]. 图书情报知识, 2014(2): 111-119.
[2] (Li Gang, Chen Jinghao.A Review of Network Public Opinion for Unexpected Emergency[J]. Document, Informaiton & Knowledge, 2014(2): 111-119.)
[3] 杨成明. 微博客用户行为特征实证分析[J]. 图书情报工作, 2011, 55(12): 21-25.
[3] (Yang Chengming.Empirical Analysis of Microblog Users’ Behavioral Characteristics[J]. Library and Information Service, 2011, 55(12): 21-25.)
[4] 彭希羡, 朱庆华, 刘璇. 微博客用户特征分析及分类研究——以“新浪微博”为例[J]. 情报科学, 2015, 33(1): 69-75.
[4] (Peng Xixian, Zhu Qinghua, Liu Xuan.Research on Behavior Characteristics and Classification of Micro-blog Users——Taking “Sina Micro-blog” as an Example[J]. Information Science, 2015, 33(1): 69-75.)
[5] 赵蓉英, 曾宪琴. 微博信息传播的影响因素研究分析[J]. 情报理论与实践, 2014, 37(3): 58-63.
[5] (Zhao Rongying, Zeng Xianqin.Micro-blog Information Dissemination Factor Analysis[J]. Information Studies: Theory & Appliction, 2014, 37(3): 58-63.)
[6] Agichtein E, Brill E, Dumais S.Improving Web Search Ranking by Incorporating User Behavior Information[C]. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2006: 19-26.
[7] Benevenuto F, Rodrigues T, Cha M, et al.Characterizing User Behavior in Online Social Networks [C]. In: Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement. ACM, 2009: 49-62.
[8] Ye S, Wu S F.Measuring Message Propagation and Social Influence on Twitter. Com[M]. Springer Berlin Heidelberg, 2010.
[9] 陈慧娟, 郑啸, 陈欣. 微博网络信息传播研究综述[J]. 计算机应用研究, 2014, 31(2): 333-338.
[9] (Chen Huijuan, Zheng Xiao, Chen Xin.Survey on Information Diffusion in Microblog[J]. Application Research of Computers, 2014, 31(2): 333-338.)
[10] 宋恩梅, 左慧慧. 新浪微博中的“权威”与“人气”: 以社会网络分析为方法[J]. 图书情报知识, 2012(3): 43-54.
[10] (Song Enmei, Zuo Huihui.Authority and Popularity: Social Network Analysis on Sina Microblogging[J]. Document, Information & Knowledge, 2012(3): 43-54.)
[11] 平亮, 宗利永. 基于社会网络中心性分析的微博信息传播研究——以Sina微博为例[J]. 图书情报知识, 2010(6): 92-97.
[11] (Ping Liang, Zong Liyong.Research on Microblog Information Dissemination Based on SNA Centrality Analysis ——A Case Study with Sina Microblog[J]. Document, Informaiton & Knowledge, 2010(6): 92-97.)
[12] 康伟. 突发事件舆情传播的社会网络结构测度与分析——基于“11·16校车事故”的实证研究[J]. 中国软科学, 2012(7): 169-178.
[12] (Kang Wei.Measurement and Analysis of Public Opinion Spread in Emergencies Based on the Social Network Theory: An Empirical Study on November 16 School Bus Accident[J]. China Soft Science, 2012(7): 169-178.)
[13] Kwak H, Lee C, Park H, et al.What is Twitter, A Social Network or A News Media?[C]. In: Proceedings of the 19th International Conference on World Wide Web. ACM, 2010: 591-600.
[14] Mislove A, Marcon M, Gummadi K P, et al.Measurement and Analysis of Online Social Networks [C]. In: Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement. ACM, 2007: 29-42.
[15] Hui-Ye C T, Chen C C, Joung Y J, et al. A Study of Blog Networks to Determine Online Social Network Properties from the Tie Strength Perspective[J]. Online Information Review, 2014, 38(3): 381-398.
[16] Java A, Song X, Finin T, et al.Why We Twitter: Understanding Microblogging Usage and Communities[C]. In: Proceedings of the 9th WebKDD Workshop on Web Mining and Social Network Analysis. ACM, 2007: 56-65.
[17] 哈罗德.拉斯韦尔. 社会传播的结构与功能[M]. 何道宽译. 北京: 中国传媒大学出版社, 2013: 11-78.
[17] (Lasswell H.The Structure and Function of Communication in Society[M]. Translated by He Daokuan. Beijing: Communication University of China Press, 2013: 11-78.)
[18] McCombs M E, Shaw D L. The Agenda-setting Function of Mass Media[J]. Public Opinion Quarterly, 1972, 36(2): 176-187.
[19] Severin W J, Jr Tankard J W. 传播理论: 起源、方法与应用[M]. 郭镇之译. 北京: 中国传媒大学出版, 2006: 110-180.
[19] (Severin W J, Jr Tankard J W. Communication Theories: Origins, Methods and Uses in the Mass Media [M]. Translated by Guo Zhenzhi. Beijing: Communication University of China Press, 2006: 110-180.)
[20] 林琛. 微博个体信息传播影响力评价指标分析[J]. 图书情报工作, 2014, 58(1): 40-43.
[20] (Lin Chen.Analysis on Evaluation Indexes of Information Dissemination Impact of Micro-blog Individual[J]. Library and Information Service, 2014, 58(1): 40-43.)
[21] Wang R, Jin Y.An Empirical Study on the Relationship Between the Followers’ Number and Influence of Microblogging [C]. In: Proceedings of the 2010 International Conference on E-Business and E-Government. 2010: 2014-2017.
[22] Krishnamurthy B, Gillp P, Arlitt M. A Few Chirps About Twitter [EB/OL]. [2016-04-07]. .
[23] Huberman B A, Romero D M, Fang W. Social Networks that Matter: Twitter Under the Microscope [EB/OL]. [2016- 04-07]. .
[24] 胡媛. 微博客中基于时序的非正式信息流机制研究——以Sina微博为例[J]. 图书情报知识, 2011(4): 111-117.
[24] (Hu Yuan.Informal Information Flow Mechanism Based on Timing of Micro-blog——Example of Sina Mocro-blog[J]. Document, Informaiton & Knowledge, 2011(4): 111-117. )
[25] 兰月新, 董希琳, 苏国强, 等. 公共危机事件网络谣言对网络舆情的影响研究[J]. 图书情报工作, 2014, 58(9): 78-84, 90.
[25] (Lan Yuexin, Dong Xilin, Su Guoqiang, et al.Study on the Influence of Internet Rumors in Public Crisis on Network Public Opinion[J]. Library and Information Service, 2014, 58(9): 78-84, 90.)
[26] 王晓光. 微博客用户行为特征与关系特征实证分析——以“新浪微博”为例[J]. 图书情报工作, 2010, 54(14): 66-70.
[26] (Wang Xiaoguang.Empirical Analysis on Behavior Characteristics and Relation Characteristics of Micro-blog Users——Take “Sina Micro-blog” for Example[J]. Library and Information Service, 2010, 54(14): 66-70.)
[27] 麦克斯韦尔-麦考姆斯, 郭镇之, 邓理峰. 议程设置理论概览: 过去, 现在与未来[J]. 新闻大学, 2007(3): 55-67.
[27] (McCombs M, Guo Zhenzhi, Deng Lifeng, et al. Overview of Agenda Setting Theory: Past, Present and Future[J]. Journalism Bimonthly, 2007(3): 55-67.)
[28] Goncalves B, Perra N, Vespignani A.Modeling Users’ Activity on Twitter Networks: Validation of Dunbar’s Number[J]. PLoS One, 2011, 6(8): e22656.
[29] Terpstra T, De Vries A, Stronkman R, et al.Towards a Realtime Twitter Analysis During Crises for Operational Crisis Management[M]. Simon Fraser University, 2012.
[30] Bosch H, Thom D, Heimerl F, et al.Scatterblogs2: Real-time Monitoring of Microblog Messages Through User-guided Filtering[J]. IEEE Transactions on Visualization and Computer Graphics, 2013, 19(12): 2022-2031.
[31] 刘坤, 尤永. “意见领袖”理论研究综述[J]. 青年记者, 2009(24): 42.
[31] (Liu Kun, You Yong. “Opinion Leaders” Theory Research[J]. Youth Journalist, 2009(24): 42.)
[31] Kim S H, Scheufele D A, Shanahan J.Think About It This Way: Attribute Agenda-setting Function of the Press and the Public’s Evaluation of a Local Issue [J]. Journalism & Mass Communication Quarterly, 2002, 79(1): 7-25.
[32] Weaver D H.Political Issues and Voter Need for Orientation [A].// The Emergence of American Political Issues [M]. The Agenda-Setting Function of the Press, 1977: 107-119.
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