By Gloria Gu, Class of 2027
We tend to think of politics in grand terms. Elite factions. Dynasties. Who wins the election. Protests. Revolutions. Mass movements that make headlines.
But what about the small stuff? A citizen writing to complain about a noisy neighbor. Someone copying and pasting a letter template they found online. A tired bureaucrat glancing at a complaint and deciding, in a split second, whether to take it seriously.
This, too, is politics. The everyday. The mundane. The moments that never make the news, but shape how millions of people experience the state.
Valerie Li studies these moments. Now an Assistant Professor of Computational Social Science at Duke Kunshan University, she holds a dual-title Ph.D. in Political Science and Social Data Analytics from Penn State. Her research draws on large-scale data: hundreds of thousands of citizen-written texts, petitions, and complaints, to examine how ordinary Chinese engage with the state in their daily lives.
This is the world of everyday politics.
From Spectacle to Everyday — Turning Toward the Ordinary
Research on Chinese politics has often devoted substantial attention to highly visible political events, such as large-scale protests. But such kind of entry points often fails to capture the full range of civic activities and political participation unfolding in China.
Coming from China herself and having spent years studying the country, Li sees things differently. “The really interesting things are happening on a daily basis in everyday politics,” she says. “Not big events, but small, isolated incidents that happen around us every day.”
Her dissertation project, “The Dynamics of Digital Claims-Making Under Authoritarian Rule,” explores how ordinary people engage in politics through everyday digital actions: filing complaints, signing petitions, and sharing grievances online. These acts are often dismissed as “low-effort” participation.
But for Li, they represent something far more significant. Contacting government officials, she emphasizes, is for many citizens their first encounter with politics. It is also a moment when they begin to realize that politics matters in their lives.
“People start to make a request, which is at least an attempt to have their demands addressed,” she says. “That’s the early stage of a robust civil society.” Even the most mundane forms of digital participation are strategic and politically consequential. They reshape how we understand state-society interaction in the digital age.
Computational Methods — An Algorithm for the Invisible
Multiply these small political acts across thousands of cities and millions of citizens in China, and the scale becomes staggering.
To make sense of everyday politics at this scale, Li needed computational tools. The method she is most proud of, is the Text Reuse Algorithm.
“Essentially, this algorithm is able to detect copy and pasting between text passages.” It resembles a plagiarism detector, but for political text rather than student homework. Originally developed for U.S. congressional studies, the algorithm was used to examine parliamentary bills and legislative writing.
Scholars noticed that legislators sometimes copy and paste from one another, a phenomenon known as policy diffusion, where lawmakers borrow and spread policy ideas. The text reuse algorithm allowed researchers to detect, at scale, which legislator borrowed from whom.
Li took this same algorithm and applied it to Chinese politics, specifically, ordinary citizens and the letters they write to local governments. “What I am interested here is about how citizens connect ideas, how ideas diffuse across citizens through the manifestation of writing these letters to their governments,” she explains.
What makes this algorithm so effective for this purpose?
Traditional keyword searches capture individual terms, but they lose context and miss the subtle variations in how ideas are borrowed and adapted.
The text reuse algorithm, by contrast, detects paragraph-level similarities and is forgiving of small modifications. “You copy my letter, but you made small modifications to those things that I write because you also have your own original ideas,” Li explains. “This algorithm can also capture that small modification in the middle and tell me, the researcher: ‘Hey, someone copied most of the text, but kept these two things as his or her original thought.'”
This algorithm helped her open a window into a world that had long remained invisible: how citizens, otherwise isolated from one another, learn, borrow, and adapt. It revealed that even in the absence of formal coordination, ideas travel. The quiet diffusion of everyday grievances, captured at scale, became visible.
State Responsiveness —How the State Reads Citizens
When citizens participate at one end of everyday politics, how does the government respond to those efforts on the other side?
For Li, the government side of the equation is just as important as the citizen side. “Another phenomenon I want to understand,” she says, “is the government side story.”
She starts with a conceptual distinction: Response versus Responsiveness. A response is simply a reply. It’s just an acknowledgment that a letter was received. Responsiveness, on the other hand, refers to the quality of that reply. Does it actually solve the problem? Or is it just polite rhetoric that leads nowhere?
“Sometimes government officials reply nicely,” Li explains. “They say, ‘We understand your issue, we are very sorry’, but they don’t actually do anything concrete. Or they politely refer you to one department, then another, then another, and the problem never gets solved.” That is good response, but low responsiveness.
But why do some demands get substantive solutions, while others get ignored?
Her analysis revealed three distinct patterns. First, an individual who submits the same request over and over again, “someone super annoying who goes to the government department every day,” as she puts it, gets the worst response. Repetition without coordination is just noise.
Second, a group that coordinates but merely copies and pastes the same template without adding any personal content gets reduced to “just one request.” The government does not see a collective movement. It sees a single demand. And it responds accordingly with indifference.
Third, the highest responsiveness occurs when collective effort and individual investment are combined. When a group unites, and each participant adds their own voice, their own circumstances, their own evidence, then the government takes it seriously.
Seemingly, collective action alone and individual effort alone both fall short; only their combination signals genuine concern that the government cannot ignore.
Given these variations in government responsiveness, citizens naturally begin to think strategically about how they present their demands. If the state responds not to numbers alone, but to signals, then what signals should citizens send? How should they frame their requests to maximize their chances of being heard?
This is precisely what Li explores in her article, “Performing Loyalty: Does Adopting State Rhetoric Make Citizen’s Demands-making More Successful?”. She observes that some people, wanting to sound more formal and make their requests appear more serious, often quote the President, cite government documents, or reference regulatory and legal provisions.
This rhetorical strategy, she suspected, might be a way to increase their chances of success. If you speak the language of the state, the logic goes, the state will reward loyalty and be more accommodating.
Li tested this assumption by using text data from China’s Mayor’s Mailbox, a digital petition platform where citizens appeal to local leaders.
The findings upended the intuitive logic. Citizens who adopted state rhetoric were less likely to receive a substantive response. Rather than improving their chances, the strategy backfired.
Li acknowledges that the relationship is complicated. Part of the explanation lies in a self-selection effect: people tend to use rhetorical strategies for issues that are already difficult to resolve, while simple problems are expressed plainly.
However, even after controlling for this self-selection statistically, she still finds that rhetorical strategy itself is harmful.
She attributes this to the signal it sends: to bureaucrats, highly formalized official language, instead of conveying sincerity, can make a request appear more strategic or adversarial, which may reduce officials’ willingness to prioritize it.
Li reveals the hidden logic of everyday politics. A thousand identical letters say nothing. A hundred letters, each with a personal story, say everything. A letter filled with official rhetoric may say less than the citizen intended. The state is listening, but not always for what citizens think it is listening for.
Fieldwork — Opening the Black Box in Beijing
Li had analyzed over 200,000 complaints, identified patterns, and built theories about how citizens coordinate and how the state responds. The empirical results were solid. But something still bothered her.
“I don’t know yet if all my theories are true in this black box process of government responsiveness,” she admits. “So why don’t I just go directly talk to someone who actually works from the inside?”
So in 2023, she went to Beijing.
She wanted to understand how government officials actually process the complaints they receive every day. With help from Tsinghua University, Li conducted field trips and interviews with local bureaucrats in Beijing. Her focus was the City of Beijing’s 12345 Hotline, part of the city’s “Swift Response to Public Complaints” (接诉即办) campaign, which provided an excellent opportunity for observation.
In the city of Beijing, once a complaint is filed, the responsible official must resolve it within a short period of time (usually seven to fifteen days). Districts are ranked by satisfaction and completion rates. This system is a highly institutionalized incentive structure designed to push officials toward efficient responses.
But when Li spoke with the grassroots bureaucrats who handle these cases day in and day out, she discovered something her data could never have told her.
“Bureaucrats are human too,” she says. “They are so tired.” Processing complaints, she learned, is not their primary job. Instead, it is an extra burden layered on top of their regular responsibilities. They are overwhelmed. They cannot possibly read every request in detail.
This led her to a crucial insight: bureaucrats rely on heuristics, mental shortcuts, to make decisions. They scan for cues, making a split-second judgment about which cases appear more urgent, consequential, or likely to require follow-up.
This is why citizens’ expressions matter. The language they use, the way they frame their concerns, and above all, the level of sincerity they convey. All of this becomes a signal read by an official with limited time and energy. Some signals attract attention; others invite dismissal.
Li’s theory, grounded in large-scale data, had already pointed in this direction. But it was the fieldwork that showed her why.
Everyday politics, she came to understand, is a signaling game.
Citizens, in the sincerity of their writing and the way they frame their concerns, send signals about who they are and what they want. Bureaucrats, in turn, read these signals and make decisions about whether to respond. The outcome of a complaint often hinges on this quiet, unseen exchange.
A New Chapter — Teaching, Community, and the Road Ahead
Li just joined DKU this year, and she looks forward to the new semester with great anticipation.
Aside from teaching computational methods that help students navigate today’s AI-driven world, she also wants to ease the panic over AI’s potential impact on the job market.
If there is one takeaway from Li’s research on state-society relations, it is this: important social and political activities remain human-centered. Behind every interaction is a person, with demeanor, emotion, and personal stories that AI cannot fully replace.
These are not new questions, but AI has made them urgent. Nobody, Li notes, fully knows the social impact of AI. And that uncertainty, she believes, is precisely why students need to engage with it.
For Li, coming back to China to join DKU was a deliberate choice, CSCC was a big part of it.
“A big reason for me to be back in China is to be able to study China from within China.” She is excited about collaboration with China-based scholars and engagement with government institutions. These are the opportunities unavailable to a US-based scholar.
But what excites her most is the community. Colleagues in the Governing China Cluster and the Digital Technology and Society Cluster work on topics directly relevant to her research, and she looks forward to cross-disciplinary conversations with faculty in art, filmmaking, and other fields.
Looking ahead, Li has two major projects in the pipeline.
The first moves beyond everyday complaints to policy suggestions. She intends to investigate whether public comments on draft policies actually shape final outcomes in China, as they sometimes do in the U.S.
The second extends her Performing Loyalty research from text to performance: analyzing how political elites use facial expressions, gestures, and camera presence to project either competence or loyalty, and whether that affects public perception and career advancement.
Now, as Li begins a new chapter at DKU, also CSCC, she is ready to bring her passion, her intellectual curiosity about China, and her dedication to research into deeper explorations of political interaction.
If the world of Everyday Politics is a quiet conversation between millions of citizens and the state, Li is determined to keep listening, thinking, and to help others hear it.