A significant share of political discourse occurs online on social media platforms. Policymakers and researchers try to understand the role of social media design in shaping the quality of political discourse around the globe. In the past decades, scholarship on political discourse theory has produced distinct characteristics of different types of prominent political rhetoric such as deliberative, civic, or demagogic discourse. This study investigates the relationship between social media reaction mechanisms (i.e., upvotes, downvotes) and political rhetoric in user discussions by engaging in an in-depth conceptual analysis of political discourse theory. First, we analyze 155 million user comments in 55 political subforums on Reddit between 2010 and 2018 to explore whether users’ style of political discussion aligns with the essential components of deliberative, civic, and demagogic discourse. Second, we perform a quantitative study that combines confirmatory factor analysis with difference in differences models to explore whether different reaction mechanism schemes (e.g., upvotes only, upvotes and downvotes, no reaction mechanisms) correspond with political user discussion that is more or less characteristic of deliberative, civic, or demagogic discourse. We produce three main takeaways. First, despite being “ideal constructs of political rhetoric,” we find that political discourse theories describe political discussions on Reddit to a large extent. Second, we find that discussions in subforums with only upvotes, or both up- and downvotes are associated with user discourse that is more deliberate and civic. Third, and perhaps most strikingly, social media discussions are most demagogic in subreddits with no reaction mechanisms at all. These findings offer valuable contributions for ongoing policy discussions on the relationship between social media interface design and respectful political discussion among users.1

The Chinese Social Credit System (SCS) is a digital sociotechnical credit system that rewards and sanctions economic and social behaviors of individuals and companies. As a complex and transformative digital credit system, the SCS uses digital communication channels to inform the Chinese public about behaviors that lead to reward or sanction. Since 2017, the Chinese government has been publishing "blameworthy" and "praiseworthy" role model narratives of ordinary Chinese citizens on its central SCS information platform creditchina.gov.cn. Across many cultures, role model narratives are a known instrument to convey "appropriate" and "inappropriate" social norms. Using a directed content analysis methodology, we study the SCS-specific social norms embedded in 100 "praiseworthy" and 100 "blameworthy" role model narratives published on creditchina.gov.cn. "Blameworthy" role model narratives stress social norms associated with an "immoral" SCS identity label termed "Lao Lai" - a "moral foe" that fails to repay debt. SCS role model narratives familiarize Chinese society with SCS-specific measures such as digital surveillance, public shaming, and disproportionate punishment. Our study makes progress towards understanding how a state-run sociotechnical credit system combines digital tools with culturally familiar customs to propagate "blameworthy" and "praiseworthy" identities.

Social media platforms generate user profiles to recommend informational resources including targeted advertisements. The technical possibilities of user profiling methods go beyond the classification of individuals into types of potential customers. They enable the transformation of implicit identity claims of individuals into explicit declarations of identity. As such, a key ethical challenge of social media profiling is that it stands in contrast with people's ability to self-determine autonomously, a core principle of the right to informational self-determination.

The Chinese Social Credit System (SCS) is a novel digital socio-technical credit system. The SCS aims to regulate societal behavior by reputational and material devices. Scholarship on the SCS has offered a variety of legal and theoretical perspectives. However, little is known about its actual implementation. Here, we provide the first comprehensive empirical study of digital blacklists (listing "bad" behavior) and redlists (listing "good" behavior) in the Chinese SCS. Based on a unique data set of reputational blacklists and redlists in 30 Chinese provincial-level administrative divisions (ADs), we show the diversity, flexibility, and comprehensiveness of the SCS listing infrastructure. First, our results demonstrate that the Chinese SCS unfolds in a highly diversified manner: we find differences in accessibility, interface design and credit information across provincial-level SCS blacklists and redlists. Second, SCS listings are flexible. During the COVID-19 outbreak, we observe a swift addition of blacklists and redlists that helps strengthen the compliance with coronavirus-related norms and regulations. Third, the SCS listing infrastructure is comprehensive. Overall, we identify 273 blacklists and 154 redlists across provincial-level ADs. Our blacklist and redlist taxonomy highlights that the SCS listing infrastructure prioritizes law enforcement and industry regulations. We also identify redlists that reward political and moral behavior. Our study substantiates the enormous scale and diversity of the Chinese SCS and puts the debate on its reach and societal impact on firmer ground. Finally, we initiate a discussion on the ethical dimensions of data-driven research on the SCS.