Author Interview: Q and A with Dr Fan Liang on The making of “good” Citizen: China’s Social Credit Systems and infrastructures of social quantification

Fan Liang

Dr. Fan Liang is an Assistant Professor of Media at Duke Kunshan University. His research focuses on the intersection of digital media, political communication, technology governance, and computational social science. His work recognizes that the modes of power have significantly shifted in the era of algorithms, big data, and social media, and examines how new communication technologies construct social and political changes, as well as how social and political powers shape and regulate the design and operation of such technologies. The finding of Dr. Liang’s research contributes to the ongoing debate about the political and social implications of technological change.

Recently, Dr. Fan Liang has published 2 journal articles. We will highlight the paper titled The making of “good” Citizen: China’s Social Credit Systems and infrastructures of social quantification, which was published in Policy & Internet.


Could you quickly explain the paper and tell us what you found?

This study examines China’s emerging Social Credit Systems (SCSs) from the perspective of social quantification. The SCS is one of China’s most ambitious policies aimed to assess and monitor the This study examines China’s emerging Social Credit Systems (SCSs) from the perspective of social quantification. The SCS is one of China’s most ambitious policies aimed to assess and monitor the performance of individuals, business entities, and governments. It is also a data infrastructure that aggregates massive datasets. In this paper, we analyze the implementation of the SCS in over 50 Chinese cities to understand how states track and assess citizens and what metrics are used for credit scoring. We find that local SCS has been designed as social quantification practices that involve two facets: a normative apparatus encouraging good citizens and social morality, and a regulative apparatus disciplining deviant behaviors and enforcing social management. As such, citizens are increasingly reconfigured as data subjects that can be measured, compared, and governed. More importantly, the system could define what is a good citizen and thus nudge people towards desired behaviors defined by the state.

How did you become interested in the study of China’s Social Credit Systems (SCSs)?

I started to investigate the SCS in 2017 when I observed the contradictory views about the SCS in news media. In fact, Western media and policymakers regularly view the SCS as a cautionary tale of surveillance and state repression in the information age. Yet, other countries and tech firms have already launched similar systems, such as the risk scores in the U.S., iBorderCtrl in the EU, and Aadhaar in India. I realized that big data and information technology have become the major approach for both states and private sectors to track and assess individuals, and the SCS is a fascinating case. Therefore, I began to study how the SCS has been designed by the government, how states collaborate with tech firms for collecting behavioral data, and how individuals have been profoundly datafied and quantified.

What methods have been used in the research?

This study relies on policy documentation, official regulations and platforms, news coverage, and gray literature and adopts policy implementation method to examine how the SCS is designed and implemented, and what are the possible consequences. In particular, we considered the SCSs as a centrally coordinated policy process by which municipal governments need to follow the chain of command from central policymakers and meanwhile design local experiments. We first read policies about quantification practices, paying close attention to the processes and indicators of calculating credit scores. We also considered the indicators used for credit assessment as a way to reverse‐engineer political logic embedded in the SCS, as they imply how political goals are imposed into social quantification to define what might be a good citizen. We thus identified these indicators mentioned in our data. Finally, we analyzed how official policies and news media discussed the potential implications of the SCSs, particularly the reward and punishment mechanisms.

What roles do students play in your current research projects? What can they learn from being in these roles?

Students plays two roles in my current research. First, some freshmen and sophomores are interested in new media studies, but they lack the necessary experience and knowledge. As such, they participate in some of my ongoing projects as research assistants to learn how to conduct academic research. For example, they are responsible for collecting data, doing observations, and conducting interviews. I hope they will be able to understand the process of doing research and grasp some skills and knowledge for new media studies. Second, I consider junior and senior students as collaborators and encourage them to develop their own projects. For instance, Yujia Zhai, a senior student majoring in Media and Arts, had some thoughts about people’s experience with digital technologies. So we conducted a CSCC-supported study to explore how people make sense of recommendation algorithms, and she presented our findings at the 2022 ICA Conference in May 2022. Based on this study, Yujia found that a new type of player – MCNs (multi-channel networks) – is increasingly emerging in Chinese digital platforms. Currently, we are working on the second project to examine the MCN industry in China.

Can you tell us your future research goals?

Currently, I’m working with several undergraduates on two projects. In the first study, we investigate a crucial actor in China’s Wanghong and livestream industries – MCNs (multi-channel networks). MCNs are entities that collaborate with Wanghong on digital platforms to support the production, promotion, management, and monetization of creative content. Focusing on industry analysis and court documents, we explore the conflicts between MCNs and Wanghong. In addition, the second project draws on human-machine communication to examine how people interact with smart speakers and virtual assistants in China.

In the future, I plan to conduct research to understand how automated decision-making has been incorporated into administrative processes and social governance, as well as how this shift affects the relationship between states and citizens.