Search for contacts, projects,
courses and publications

Reconciliation or Polarization: A Case Study of the Pattern of Online Opinion Evolution on Controversial Issues



Balbi G.


Jiang S.




There are two opposite views of the consequence of opinion evolution on controversial issues: one assumes that the initially diverse opinions can eventually reach to a somehow consensus via constructive and sensible debates in public sphere（Habermas，1962）, while the other predicts a self-reinforced process of opinion polarization (Sunstein, 2003). Both scenarios seem theoretically possible and empirically observable. What's lacked so far, however, is some convincing explanation of the underlying mechanism that defines the patterns of opinion evolution. 

One typical case in China is the debate on GMO (genetically modified organism). GMO is a focal and significant issue of agriculture in China, but arguments never stopped since its emergence. People participating the discussion form two camps: pro-GMO and anti-GMO groups. Continuous disputes and controversies have lasted since the advent of this issue, with the prominence reached its peak when from September 2013 to February 2014，when Fang Zhouzi, a scientist and science popularization writer, and Cui Yongyuan, a media professional, was both profoundly engaged in the debating as the leaders of pro- and anti- GMO campuses. The public debating has become highly visible to the world thanks to the social media platforms such as Tencent Weibo. In this specific case, the fierce debating ended with polarization rather than reconciliation (Jia, Fan & Yan, 2015).

Three years later, another event related to GMO, which could not be ignored is that Heilongjiang province issued a prohibition regulation of planting, selling GMO, December 16 2016. Since officially announced, it aroused heated discussions, diverse opinions rapidly forming two different views as well: support and oppose, both with strong emotions. So far, reconciliation has not reached.

Current state of the research in the field

Evidence suggests that online public opinion has become a competing force, influencing both the issue agendas of the traditional media and the government at the national level in the Chinese context (Luo, 2014). New media offers platforms and possibilities for rational open and equal discussion online, which is expected by scholars to be an effective way for democratic consultation and reaching a consensus for controversial issues (Fan et al., 2013). However, the effects of online discussion differ on different issues and for debates of GMO, a typical but special case of controversial issues, online opinions have not reached a consensus so far, both China and aboard（Jia & Fan, 2015）. Scholars point out that scientists always neglect the public concerns when they try to communicate with and talk to common people, and also there exists a cognition gap between scientist and media profession. As for the dimension of public, scientific literacy, media usage and social network all affect people attitude towards GMO. Unexpectedly, the understanding of scientific nature is negatively related to people’s trust of scientist on the issue of GMO (Jin & Chu, 2015). Government, the public, scientific communities, media and other interested parties contribute to the complexities of GMO, making it a international issue, a social issue and a political issue rather than a technique issue merely. Studies on how opinions of GMO form and change are of significance both theoretically and practically.

Current studies about the dynamic changes of online opinion on controversial issues are mainly descriptive in nature with some approaches such as social network analysis. The key determinants, which affect the course of opinion climate changes, haven't been systematically identified, and the patterns of interplays among these factors yet to be theoretically proposed (Tao & Chen, 2016).

Aim and research questions

This study aims to fulfill the gap through a close investigation of a highly controversial issue, i.e., public's perception of GMO, via the approach of case study. More specifically, we hope to explore the answers of following questions:

(1)               Are opinions doomed to polarize on controversial issues? For the realization of reconciliation, what are the supposed prerequisites?  

(2)               Among the institutional factors shaping the progress of online debating, what the platforms, as well as the governmental departments can do in order to facilitate a more constructive debating which might eventually lead to reconciliation?

(3)               Do people who involved in controversial debate especially the leaders of different camps have something in common? How can they affect the trend of debate?

(4)               Is there any difference between China and other western countries of public opinion formation and debates on controversial issues?

(5)               What is the landscape of Internet values on contemporary China and how it affects China’s civil society?  


I might mainly employ in-depth interview as the chief way of data collection in the process of case study, with the supplemental analysis of discourses and texts of both sides. The potential interviewees include about 20 people who were engaged in the debate or act as key nodes in the information diffusion networks of both sides, and staffs from Weibo or other online forums, in order to probe new media platforms’ attitudes and functions during the process. Additionally, approximately 20 netizens from Swiss are my target interviewees, for later comparisons.

In terms of the discourse analysis, two parts are included. I will mainly investigate:

(1)                  The posts and their relevant comments of Fang Zhouzi and Cui Yongyuan on Tencent, a microblogging platform, and Tianya (, a BBS platform. The interval for analysis will be from September 7, 2013 to February 28, 2014.

(2)                  All relevant reports and comments of newspaper, discussions on microblog, BBS platforms and other websites about Heilongjiang’s prohibition of GMO. The interval for analysis will be from December 16, 2016 to January 16, 2017.

Additional information

Start date
End date
8 Months
External partners