Understanding the interaction of politics, economy and society in China.
Overview
The appearance of a strong, monolithic Chinese state belies considerable variation in economic, cultural, and governance practice across localities, i.e., administrative jurisdictions and regions. These variations create tensions in uneven development that may exert significant impacts on political processes and regime stability, and are also sources of innovation and institutional changes. The political economy of locality sheds light on the sub-national dynamics in local governance, civil society, and the role of local bureaucratic networks and social institutions in economic development. To understand how the Chinese economy functions and evolves, we need to understand how the political economy, in general, and the political economy of locality – the interaction of politics, economy and society – works across localities, how government policies are implemented and derailed at local levels, how local initiatives take place or are suppressed, and how local bureaucrats and citizens respond to top-down mobilization. Our research is organized around two sets of activities: a.) the collection and analysis of micro-level data to systematically examine variations across localities at the intersection of politics and economy; b.) collaboration with local researchers to gain insights into behavioral patterns in local response to government policies and initiatives.
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How do state-controlled broadcasters reach foreign publics to engage in public diplomacy in the era of social media? Previous research suggests that features unique to social media, such as the ability to engage in two-way communication with audiences, provide state-controlled broadcasters new opportunities for online public diplomacy. In this paper, we examine what strategies were used by four Chinese state-controlled media outlets on Twitter to reach foreign publics as the Chinese Communist Party worked to expand its public diplomacy and international media outreach efforts. We find that all outlets increased the volume and diversity of content while none engaged in interactive, two-way communication with audiences, and none appeared to artificially inflate their follower count. One outlet, China Global Television Network, made outsized gains in followership, and it differs from the other Chinese outlets in that it was rebranded, it disseminated a relatively lower share of government-mandated narratives pertaining to China, and the tone of its reporting was more negative. These results show that during a period when Chinese state-controlled broadcasters gained followers on Twitter, outlets made limited use of features unique to social media and instead primarily used social media as a broadcast channel.
We study the effect of a victimization narrative on national identity and public opinion in China experimentally. Previous research has suggested that governments can shape public opinion by guiding citizens’ collective memories of historical events, but few studies have established a clear causal link. By conducting an online survey experiment among 1890 urban Chinese citizens, we examine the causal impact of historical narratives on political attitudes. We find that, compared to control conditions, a narrative focusing on China’s humiliating past in the late Qing significantly reinforces respondents’ attachment to the victim side of the Chinese national identity, raises suspicion of the intention of foreign governments in international disputes, stimulates preference for more hawkish foreign policies, and strengthens support for China’s current political system. These effects are particularly strong among respondents without a college degree.
The International Journal of Press/Politics,
August 8, 2022
Government censorship—internet shutdowns, blockages, firewalls—impose significant barriers to the transnational flow of information despite the connective power of digital technologies. In this paper, we examine whether and how information flows across borders despite government censorship. We develop a semi-automated system that combines deep learning and human annotation to find co-occurring content across different social media platforms and languages. We use this system to detect co-occurring content between Twitter and Sina Weibo as Covid-19 spread globally, and we conduct in-depth investigations of co-occurring content to identify those that constitute an inflow of information from the global information ecosystem into China. We find that approximately one-fourth of content with relevance for China that gains widespread public attention on Twitter makes its way to Weibo. Unsurprisingly, Chinese state-controlled media and commercialized domestic media play a dominant role in facilitating these inflows of information. However, we find that Weibo users without traditional media or government affiliations are also an important mechanism for transmitting information into China. These results imply that while censorship combined with media control provide substantial leeway for the government to set the agenda, social media provides opportunities for non-institutional actors to influence the information environment. Methodologically, the system we develop offers a new approach for the quantitative analysis of cross-platform and cross-lingual communication.
Repression research examines the causes and consequences of actions or policies that are meant to, or actually do, raise the costs of activism, protest, and/or social movement activity. The rise of digital and social media has brought substantial increases in attention to the repression of digital activists and movements and/or to the use of digital tools in repression, which is spread across many disciplines and areas of study. We organize and review this growing welter of research under the concept of digital repression by expanding a typology that distinguishes actions based on actor type, whether actions are overt or covert, and whether behaviors are shaped by coercion or channeling. This delineation between broadly different forms of digital repression allows researchers to develop expectations about digital repression, better understand what is “new” about digital repression in terms of explanatory factors, and better understand the consequences of digital repression.
