|本期目录/Table of Contents|

[1]陈安繁,罗 晨,胡 勇,等.中国社交媒体上转基因争论的网络议程研究[J].未来传播(浙江传媒学院学报),2020,(04):8-20.
 Chen Anfan,Luo Chen,Hu Yong,et al.Research on the Internet Agenda of Transgenic Debate in Chinese Social Media[J].FUTURE COMMUNICATION,2020,(04):8-20.
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中国社交媒体上转基因争论的网络议程研究()
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《未来传播》(浙江传媒学院学报)[ISSN:2096-8418/CN:33-1334/G2]

卷:
期数:
2020年04期
页码:
8-20
栏目:
媒介社会
出版日期:
2020-08-15

文章信息/Info

Title:
Research on the Internet Agenda of Transgenic Debate in Chinese Social Media
文章编号:
2096-8418(2020)04-0008-13
作者:
陈安繁 罗 晨 胡 勇 徐靖杨 徐永妍
陈安繁,中国科学技术大学 人文与社会科学学院,安徽 合肥,230026; 罗晨,清华大学 新闻与传播学院,北京,100091; 胡勇,北京理工大学 北京市海量语言信息处理与云计算应用工程技术研究中心,北京,100081; 徐靖杨,中国科学技术大学 人文与社会科学学院,安徽 合肥,230026; 徐永妍,中国科学技术大学 人文与社会科学学院,安徽 合肥,230026;
Author(s):
Chen Anfan Luo Chen Hu Yong Xu Jingyang Xu Yongyan
关键词:
转基因 社交媒体 网络议程设置
分类号:
G206
DOI:
-
文献标志码:
A
摘要:
本研究聚焦于新浪微博上转基因争论的议题,采用第三级议程设置的方法,检验了不同议程设置主体之间议程的关系,其发现主要有:(1)挺转群体与反转群体的议程不可通约,中立群体扮演了挺转与反转两个极端之间缓冲地带的角色;(2)普通用户与认证个人用户的议程深度耦合,但和认证机构用户的议程脱钩;(3)普通用户与反转群体议程高度正相关,说明普通用户更偏向持反转立场,而认证个人用户偏向持中立立场,认证机构用户的议程中,中立与挺转立场并存;(4)网络身份相较于对转基因的态度更容易瓦解对话的有效性。在中国社交媒体空间中,挺转与反转的尖锐对立与其说是一场针锋相对的“数字加沙地带”,毋宁可界定为“鸡同鸭讲”的“数字柏林墙”。

参考文献/References:

[1]Guo, L., Rohde, J. A., & Wu, H. D.(2020). Who is resposible for Twitter's echo chamber problem? Evidence from 2016 U.S. election networks. Information, Communication & Society, 23(2):234-251.
[2]Li, Y., Luo, C., & Chen, A.(2019). The evolution of online discussions about GMOs in China over the past decade: Changes, causes and characteristics. Cultures of Science, 2(4):311-325.
[3]Landrum, A. R., Hallman, W. K., & Jamieson, K. H.(2019). Examining the impact of expert voices: Communicating the scientific consensus on genetically-modified organisms. Environmental Communication, 13(1):51-70.
[4]Cao, C.(2018). GMO China: how global debates transformed China's agricultural biotechnology policies. Columbia University Press.
[5]苗伟山,贾鹤鹏.社交媒体中转基因食品的媒介框架研究——基于美国youtube视频网站的案例分析[J]. 科普研究,2014(5).
[6]陈安繁,金兼斌,罗晨.奖赏与惩罚:社交媒体中网络用户身份与情感表达的双重结构[J]. 新闻界,2019(4).
[7] Cui, K., & Shoemaker, S. P.(2018). Public perception of genetically-modified(GM)food: A nationwide chinese consumer study. Npj Science of Food, 2(1):10.
[8]Huang, J., Peng, B., & Wang, X.(2017). Scientists' attitudes toward agricultural GM technology development and GM food in China. China Agricultural Economic Review, 9(3):369-384.
[9]Guo, L., Vu, H. T., & McCombs, M.(2012). An expanded perspective on agenda-setting effects: Exploring the third level of agenda setting. Revista de Comunicacion, 6(11):51-68.
[10]Chen, H. T., Guo, L., & Su, C. C.(2020). Network Agenda Setting, Partisan Selective Exposure, and Opinion Repertoire: The Effects of Pro-and Counter-Attitudinal Media in Hong Kong. Journal of Communication, 70(1):35-59.
[11]Vargo, C. J., Guo, L., McCombs, M., & Shaw, D. L.(2014). Network issue agendas on Twitter during the 2012 U.S. presidential election. Journal of Communication, 64(2):296-316.
[12]Vargo, C. J., & Guo, L.(2017). Networks, big data, and intermedia agenda setting: An analysis of traditional, partisan, and emerging online U.S. news. Journalism & Mass Communication Quarterly, 94(4):1031-1055.
[13]Chen, Z., Su, C. C., & Chen, A.(2019). Top-down or bottom-up? A network agenda-setting study of Chinese nationalism on social media. Journal of Broadcasting & Electronic Media, 63(3):512-533.
[14]Guo, L., Mays, K., & Wang, J.(2019). Whose story wins on Twitter? Visualizing the South China Sea dispute. Journalism Studies, 20(4):563-584.
[15]Guo, L., & Vargo, C. J.(2015). The power of message networks: A big-data analysis of the network agenda setting model and issue ownership. Mass Communication and Society, 18(5):557-576.
[16]Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M.(2009). Computatioal social science. Science, 323(5915):721-723.
[17]Hargittai, E.(2008). Whose space? Differences among users and non-users of social network sites. Journal of Computer-Mediated Communication, 13(1): 276-297.
[18]Himelboim, I., McCreery, S., & Smith, M.(2013). Birds of a feather tweet together: Integrating network and content analyses to examine cross-ideology exposure on Twitter. Journal of Computer-Mediated Communication, 18(2):154-174.
[19]McPherson, M., Smith-Lovin, L., & Cook, J. M.(2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27(1):415-444.
[20]Nip, J. Y. M., & Fu, K. W.(2016). Challenging official propaganda? Public opinion leaders on Sina Weibo. The China Quarterly, 225(3):122-144.
[21]Su, Y.(2019). Exploring the effect of Weibo opinion leaders on the dynamics of public opinion in China: A revisit of the two-step flow of communication. Global Media and China, 4(4):493-513.
[22]Luo, Y..(2014). The internet and agenda setting in china: the influence of online public opinion on media coverage and government policy. International Journal of Communication,8(2):1289-1312.
[23]Wen, N., & Wei, R.(2018). Examining effects of informational use of social media platforms and social capital on civic engagement regarding genetically modified foods in China. International Journal of Communication, 12(2):3729-3750.
[24]Chaiken, S., Liberman, A., & Eagly, A. H.(1989). Heuristic and systematic information processing within and beyond the persuasion context.(In)JS Uleman & JA Bargh(Eds.), Unintended thought: Limits of awareness, intention, and control.New York: Guilford,212-252.
[25]Huang, J., Peng, B., & Wang, X.(2017). Scientists' attitudes toward agricultural GM technology development and GM food in China. China Agricultural Economic Review.
[26]Yuan, S., Ma, W., & Besley, J. C.(2019). Should scientists talk about GMOs nicely? Exploring the effects of communication styles, source expertise, and preexisting attitude. Science Communication, 41(3):267-290.
[27]Blei, D. M., Ng, A. Y., & Jordan, M. I.(2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan):993-1022.
[28]刘军. 整体网分析:UCINET 软件实用指南[M].上海:格致出版社,上海:上海人民出版社,2014:280-296.
[29]Zhao, Y., Deng, H., Yu, C., & Hu, R.(2019). The Chinese public's awareness and attitudes toward genetically modified foods with different labeling.NPJ science of food,3(1):1-7.
[30]Sherman, J.(2014). Anti-GMO Strategies and Frames: Global Trends in the Growth of Resistance to GMOs, Ph.D. Dissertation. The George Washington University.

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备注/Memo

备注/Memo:
基金项目:本文系2016年国家科技重大专项“转基因生物新品种培育”课题“转基因生物技术发展科普宣传与风险交流”(2016ZX08015002)的成果。
作者简介:陈安繁,男,博士后研究员。罗晨,男,博士候选人。胡勇,男,硕士研究生。徐靖杨,男,硕士研究生。徐永妍,女,硕士研究生。
更新日期/Last Update: 2020-08-15