Intensified Clashes of Ideologies Online with Group Political Bias
Xintong Han – Concordia University and CIREQ;
Mantian (Mandy) Hu - CUHK Business School
-- Online platforms provide a forum for communicating about various ideologies, which can also intensify ideological debates and lead to polarization of opinions. Many social media platforms have gradually become battlefields for ideological clashes between different groups. In 2020, the Trump administration took various policy countermeasures against Chinese social media apps’ online ideological propaganda. Using data from Facebook, our recent paper “Intensified Clashes of Ideologies Online with Group Political Bias” is the first paper to study the online ideological conflict between pro-democracy and pro-establishment netizens, and explores the potential factors leading to the intensification of said conflict.
The protests calling for Hong Kong’s democratic autonomy have been widespread since 2019. As the protests grew, there were inevitably many clashes between protestors and the police, leading to an increasing number of news reports on police attacks. Attitudes towards the “police” became a focal point of ideological conflict: the pro-democracy camp opposes police abuse, and the establishment camp supports police activities. We collected data from Facebook’s Hong Kong media from April 2019 to April 2020. Our data include variables related to each media homepage (number of followers, number of news posts, etc.), their political tendency score (provided by the School of Journalism and Communication of the Chinese University of Hong Kong), and comments under each news post. We used the dynamic panel regression model to study how the number of pro-independence and anti-police comments evolved dynamically in relation to the increase of pro-police comments.
First, we show that support for the police greatly intensifies the pro-democracy camp’s distrust of the police. The pro-police comments, though make the offline protest riskier, also encourage netizens to express their appeals for HK autonomy more frequently. To reinforce the findings, we use instrumental variables (IVs) to tackle the potential endogeneity issues. The IVs are based on the number of new and dead Simplified Chinese accounts per day. These variables are related to the number of pro-police comments but do not directly affect the number of anti-police comments the next day. The exclusion restrictions are valid since it is almost impossible for a user to track every commenter’s history across all media outlets and determine if this is the first or last comment, as we do. The regression results indicate that the Ordinary Least Squares (OLS) method underestimates the impact of pro-police comments on both the number of pro-police comments and demands for autonomy.
Second, we find that when a pro-police comment is written in Simplified Chinese, it receives particularly strong opposite responses. Since the Simplified Chinese comments are typically pro-establishment, we further explore whether this tension arises from a political bias or the content of the comments. Further evidence indicates that the number of anti-police and pro-independence voices decreases if we remove pro-police comments from users who use Simplified Chinese only occasionally and Traditional Chinese most of the time. This means that users care more about how the comment is written than who the commenter is. The “Official Character Simplifications” reforms implemented by the People’s Republic of China in the 1950s formed a longstanding inherent bias among netizens, which intensifies the current ideological clashes online.
Lastly, we investigate why the OLS method underestimates the effect of pro-police comments. We found that nearly half of the users comment in a similar way to a bot: they are active only for one day and then disappear from the platform. We construct new variables to measure the rate of pro-police comments from the “suspected bot” in all of the daily comments beneath each piece of media. The results show that provocative comments are likely to be diluted by the comments from suspected bots, which soften the debate’s atmosphere.
Our paper provides important reference for the policies relating to Internet governance. In particular, China’s “Great Firewall” policy has long been criticized for not allowing users to freely browse foreign websites. In our paper, we find the policy’s positive aspects: First, although the policy prevents Chinese mainland netizens from visiting foreign websites, it also eases the online ideological clashes between China and the West. Second, even for those who have access to foreign websites, their ideology has not been significantly affected in the short term, and many of them are strongly pro-China.