Abstract
In information dissemination on Weibo, key nodes determine the flow and direction of information transmission and hence have a significant influence on the trend of public opinion. In this study, we looked at 7584 popular Weibo postings regarding 30 public incidents from between 2011 and 2012 with comparatively greater public impact and identified a total of 2158 key nodes and the factors that influenced such nodes. We found that different key nodes exert various influences on information dissemination within Weibo, with the top nine Weibo IDs or accounts (0.41% of the overall sample) with the highest repost and comment counts accounting for 20% of total repost and comment counts. We also found that the influence of such key nodes is determined by several factors, with factors that have a significant influence on comment and repost counts on “hot” postings being: key node type, speed of intervention; and the characteristics of the Weibo posting in question. The influence of follower count on comment and repost counts of “hot” postings is comparatively weak. In this article, we recommend that attention needs to be paid to such key nodes on Weibo, particularly nodes that occupy central positions, and to try and guide public opinion on Weibo through these nodes.
Authors: Xie Yungeng and Rong Ting. Data collection and processing: Qiao Rui; Xiong Renxia; Yao Qiong; Qin Jing; Yang Fan; Tan Xiaoyi; Zhang Hongli; Wang Lian; Li Yilin; Yuan Qiongfang; Zheng Guangjia; Chen Wei; Li Mingzhe; He Jieyan; Yang Fan; Chen Ziwei; Li Jie; Qin Xin; Wu Zhihua; Cui Min; Li Yi; Wang Weiwei; Gong Xue; Jiang Qian; Liu Yingyan; Liu Siqing; Wang Kaili, and Zhu Mengying, etc., of the Public Opinion Research Laboratory of Shanghai Jiao Tong University.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
XinhuaNet (2013).
- 2.
Qian et al. (1990).
- 3.
He et al. (2007).
- 4.
Haewoon Kwak, Changhyun Lee, Hosung Park, Sue Moon. What is Twitter, a Social Network or a News Media? International World Wide Web Conference Committee (IW3C2).
- 5.
Cha et al. (2010).
- 6.
Bongwon Suh, Lichan Hong, Peter Pirolli, and Ed H. Chi. Want to be retweeted? large scale analytics on factors impacting retweet in the Twitter network. IEEE International Conference on Social Computing/IEEE International Conference on Privacy, Security, Risk and Trust.
- 7.
Wang (2010).
- 8.
Guo et al. (2012).
- 9.
Hu and Wang (2005).
- 10.
Barabsi (2013).
References
Barabsi, A.-L. (2013). Discussion: Network science. Philosophical Transactions A: Mathematical, 371(1987).
Cha, M., Haddadi, H., Benevenuto, F., & Gummadi, K. P. (2010). Measuring user influence in twitter: The million follower fallacy. In Proceedings International AAAI Conference on Weblogs and Social Media (ICWSM).
Guo, H., Lu, Y., Wang, Y., & Zhang, L. (2012). Measuring the influence of Weibo users in information dissemination. Journal of Shandong University (Science Edition), (5), 78–83.
He, N., Li, D., Gan, W., & Zhu, X. (2007). Summary of the identification process with key nodes in complex networks. Computer Science, (12), 1–5.
Hu, H., & Wang, L. (2005). A brief history of studies in power-law distribution. Physics, (12), 890.
Qian, X., Yu, J., & Dai, R. (1990). A new discipline of science—The study of open complex giant system and its methodology. Chinese Journal of Nature, (13), 1.
Wang, X. (2010). An analysis of the relationships between the behavior and relationship characteristics of Weibo users: An example based on Sina Weibo. Library and Information Science, (14), 66–70.
XinhuaNet. (2013). Statistical report on internet development in China. January 15, 2013. http://news.xinhuanet.com/tech/2013-01/15/c_124233840.htm.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Social Sciences Academic Press
About this chapter
Cite this chapter
Xie, Y., Rong, T. (2019). Key Points in the Weibo Information Dissemination Process and Their Causal Mechanism: An Empirical Study of 30 High-Profile Opinion Incidents on Weibo. In: Xie, Y. (eds) Report on Chinese Social Opinion and Crisis Management. Research Series on the Chinese Dream and China’s Development Path. Springer, Singapore. https://doi.org/10.1007/978-981-10-4003-0_8
Download citation
DOI: https://doi.org/10.1007/978-981-10-4003-0_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-4001-6
Online ISBN: 978-981-10-4003-0
eBook Packages: Economics and FinanceEconomics and Finance (R0)