Technological advancements have had a profound influence on social science research. The rise of the internet, mobile hardware and app economies generate a breadth, depth and type of data previously unimaginable, while computational capabilities allow granular analyses that reveal patterns across massive data sets.  From these new types of data and forms of analysis, has emerged a crisis and renaissance of methodological thought.

Early excitement around big data celebrated a world that would be entirely changed and entirely knowable. Big data would “revolutionize” the way we “live, work, and think” claimed Viktor Mayer-Schönberger and Kenneth Cuckier in their 2013 monograph, which so aptly captured the cultural zeitgeist energized around this new way of knowing. At the same time, social scientists and humanities scholars expressed concern that big data would displace their rich array of methodological traditions, undermining diverse scholarly practices and forms of knowledge production. However, with the hype around big data beginning to settle, polemic visions of omnipotence on the one hand, and bleak austerity on the other, seem unlikely to come into fruition.

While big data itself enables researchers to ask new kinds of questions, I argue that big data’s most significant effect has been to bring social thinkers back to the methodological (and philosophical) drawing board. For decades, researchers have relied on the same suite of epistemological tools—survey, ethnography, interview, and census. Advances in these well-worn methods have undoubtedly increased the sophistication of knowledge production. For example, statistical analyses are more precise and complex, while ethnographers regularly integrate critical race and feminist theories into their research process. In turn, computer-based tools are now part of the quantitative and qualitative research repertoire, streamlining intricate numerical relationships and troves of field notes alike. But these innovations in qualitative and quantitative research are all, more or less, linear progressions. Big data is a move in a new direction.  Big data isn’t just about answering particular questions better, but about asking questions we didn’t even know we had. This capacity to pose and answer new kinds of questions has given pause to the myriad stakeholders interested in understanding the world and the people who live together in it—scholars, investors, politicians, scientists. In this pause, we find a renewed focus on epistemology.

Grappling with the capabilities of big data entails looking back at how we have known and looking forward, to how we might know. It pushes us to revisit what we have done, and imagine what we can now do.  Susan Halford and Mike Savage’s notion of “symphonic social science” resides neatly in this intellectual space of revisiting and reimagining that big data creates.

Recently published in the journal Sociology, Halford and Savage’s piece entitled “Speaking Sociologically with Big Data: Symphonic Social Science and the Future for Big Data Research” begins by looking back at the most influential works from the contemporary era. To learn how to best manage big data, the authors contend, we must first look at how scholars have leveraged data with optimal effectiveness in the past. That is, they look back in order to look forward. Halford and Savage identify three canonical contemporary works: Robert Putnam’s Bowling Alone, Thomas Piketty’s Capital in the Twenty-First Century and Richard Wilkinson and Kate Pickett’s The Spirit Level: Why Equality is Better for Everyone.  Though coming from different disciplines and addressing distinct social phenomena, Halford and Savage demonstrate a similar analytic approach in all three works. Namely, Putnam, Piketty, and Wilkinson and Pickett each generate an argument by compiling multiple diverse data sources, exploring those data sources with relatively simple statistics, and making an argument about the ways that the data converge on a larger, underlying point (i.e., substantial shifts in, and unequal distributions of, social and economic capital).

Halford and Savage describe this process as a symphonic, in which each data source is its own riff, and all sources return to a single refrain. In its repetition, the refrain makes a powerful and compelling case, beyond what any one data source could demonstrate on its own. In the authors’ own words:

Drawing these data together into a powerful overall argument, each book relies on the deployment of repeated ‘refrains’, just as classical music symphonies introduce and return to recurring themes, with subtle modifications, so that the symphony as a whole is more than its specific themes. This is the repertoire that symphonic social science deploys. Whereas conventional social science focuses on formal models, often trying to predict the outcomes of specific ‘dependent variables’, symphonic social science draws on a more aesthetic repertoire. Rather than the ‘parsimony’ championed in mainstream social science, what matters here is ‘prolixity’, with the clever and subtle repetition of examples of the same kind of relationship (or as Putnam (2000: 26) describes it ‘imperfect inferences from all the data we can find’) punctuated by telling counter-factuals (Halford and Savage 2017).

The symphonic data assemblage and its analysis, Halford and Savage contend, is derived from theory, exhibits clear visual representation, and can/should act as a guide for dealing with big data.

The symphonic approach instructs big data analysts to select their data points, data sets, and computational approaches through theoretical understandings of the processes they wish to unearth. This means taking a critical approach to big data, maintaining an awareness that big data are often collected for financial and/or security purposes, and may therefore be inadequate or ill equipped to answer sociological questions. It means combining data in thoughtful ways, and knowing when data are irrelevant. It means visualizations that both represent data and also, integrate into argument formation, revealing patterns to the researchers who in turn reveal patterns to consuming publics. In these ways, big data can be a rigorous complement to existing methods. Large scale computations can enrich—rather than displace—ways of knowing about the world while social theory remains central to analysis and argumentation.

Symphonic social science is both a considered approach to big data and also, an artefact of big data’s effects upon epistemology. Big data has disrupted knowledge production, focusing scholarly attention on how we have known and how we might know. In this vein, the symphonic approach can fruitfully apply not only to big data but also to new forms of established methodologies. We can imagine, for instance, a multiple case study approach to ethnography, in which each case, though rich in its own empirically grounded way, combines into an ethnographic assemblage that rings through unexpected refrains. We can imagine mixed methods designs, in which big data, survey data, and interviews each act as their own verse, which together create a powerful harmony of argument. The symphonic approach is indeed versatile and elegant. It is an important way forward, derived from looking back, inspired by big data.


Jenny Davis is on Twitter @Jenny_L_Davis

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With advances in machine learning and a growing ubiquity of “smart” technologies, questions of technological agency rise to the fore of philosophical and practical importance. Technological agency implies deep ethical questions about autonomy, ownership, and what it means to be human(e), while engendering real concerns about safety, control, and new forms of inequality. Such questions, however, hinge on a more basic one: can technology be agentic?

To have agency, technologies need to want something. Agency entails values, desires, and goals. In turn, agency entails vulnerability, in the sense that the agentic subject—the one who wants some things and does not want others—can be deprived and/or violated should those wishes be ignored.

The presence vs. absence of technological agency, though an ontologically philosophical conundrum, can only be assessed through the empirical case. In particular, agency can be found or negated through an empirical instance in which a technological object seems, quite clearly, to express some desire. Such a case arises in the WCry ransomware virus ravaging network systems as I write.

The large scale hack has left organizations around the globe unable to access important documents and data as they struggle with a quickly spreading virus that infects networks with ransomware. The virus, variously referred to as WCry, WannaCry, or Wana Decryptor, accesses networks through an unpatched security breach in the Windows operating system that persists on machines that haven’t been recently updated. Infected networks hide files and data behind a demand for substantial payment, threatening to delete important information and up the financial ante if payments are not made. Cybersecurity experts are in a frenzy trying to contain the damage, while affected organizations are scrambling to continue functionality in the absence of electronic systems that are otherwise integral to daily operation. Hospitals have been disproportionately affected, but telecom companies, car factories, and others have been hit as well. Unlike physical assets that can be locked away with a state of the art security system like the ones sold by Smart Card Store, digital security is often misunderstood and mis managed.

What the virus wants seems straightforward: money—in the form of bitcoin. This desire is made clear through an unambiguous pop-up-window with instructional text and a ticking countdown clock that indicates how much time someone has to comply before the price goes up and files are lost forever.

I argue, however, that the virus doesn’t want anything at all, because it can’t want anything. The virus doesn’t have agency, people do. What the virus has, is efficacy. Agency and efficacy with regard to technological objects are related but distinct constructs, and their place in the WCry incident presents a critical case study in how technologies work.

Ernst Schraube describes technology as materialized action.  It is the material form of agentic moves on the part of designers and users, all of whom are embedded in social, structural, and institutional infrastructures. Designers imbue technologies with particular sets of values—both implicit and explicit—derived from multiple sources, including personal history and biography, cultural trends and norms, and directives from corporate and government entities. In turn, users deploy technologies for intended, unintended, and sometimes highly unexpected purposes. Technologies are built with intention, but once a technology is out there, the makers cannot maintain control.

Schraube’s materialized action is a direct response to Actor Network Theory (ANT), which positions organisms and technologies in horizontal assemblages. In ANT, all parts of a socio-technical system hold equal influence as indicated by the shared moniker of “actant.” The arrangement of chairs, desks, and a lectern, for example, create as much as reflect power distinctions between speakers and listeners. That is, technological objects do something in their own right. Schraube begins with this technological doing posited by ANT, but diverges by prioritizing humans as a disproportionate force in the human-technology web. That is, technology is efficacious—it does something—but not agentic—it wants nothing.   

While ANT would implicate the ransomware as a subject desiring cash and information, Schraube understands that the WCry program is a materialization of competing agentic agendas: intelligence gathering by the U.S. government and financial exploitation by a criminal hacker element. The virus wants to collect neither knowledge nor money, but can efficaciously acquire both.

Spread through a network vulnerability identified and exploited by the National Security Agency (NSA), the virus is imbued with the goals and desires of this government institution. It is a technology of epistemology—a way of knowing—that includes distrust of U.S. and foreign citizens and an arrogant presumption of legitimate access to individual and organizational information via stored files and data.

With the NSA technology stolen and distributed by the group Shadow Brokers, WCry emerges as a money collection system and at the same time, a powerful symbol of organizational penetrability. It demands money while flaunting the porousness of networked systems so integral to the smooth function of public life. In these ways, the program embodies multiple meanings, infused with the agencies of authoritarian forces along with hackers and social disruptors.

These agentic moves—by the NSA, Shadow Brokers, and those who deployed the tool against hospitals, states, and corporate entities—give new agency to an object that was, already, deeply efficacious. MCry’s capacity to do cannot be denied. What it wants, however, cannot disentangle from the people who made, used, and co-opted the technology.

Conceptualizing technology as efficacious but not agentic centers a political orientation towards technology. The makers are agentic. The users are agentic. The objects are, to varying degrees, effective in carrying out maker-user agencies.   What technologies do, then, can only reflect what a particular set of people want. Understood in this way, desirable and undesirable outcomes—or effects—can be named, located, and when needed, changed. Technologies cannot take over the world, as technologies are, always, from and of us.


Jenny is on Twitter @Jenny_L_Davis

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Did I request thee, Maker, from my Clay
To mould me Man, did I sollicite thee
From darkness to promote me, or here place
In this delicious Garden?

Adam in John Milton’s, Paradise Lost 1667 (X. 743–5)

In John Milton’s Paradise Lost we see a poetic retelling of the biblical story of humanity and temptation. The excerpt above is from Adam, who mourns his fate as one who was brought into the world unwittingly, and then forsaken by his maker.   Adam blames his creator for designing a fallible subject, with vulnerabilities that manifest in the ultimate fall from grace. From this classic story of creation, willfulness, and abandonment, I can’t help but think about robots, their creators, and what happens once robots become sentient and autonomous.

Although the precise trajectory of robotic advancement is difficult to pin down,  Stephen Hawking claims that within a few decades robots will achieve sentient thought and will be able to question their existence and position in human society. With such a prospect on the (potentially quite close) horizon, legal systems have begun to think about how to classify, treat, and regulate intelligent machines.

Drafting and implementing a contingency and safety measure detailing robots’ parity and status as “electronic persons” is an avenue that the European Parliament is currently debating. If a robot were afforded legal personhood, it would hold, like that of a corporation, legal rights and obligations.

Electronic personhood as a legal status is premised on robots as intelligent beings, capable of both generating and experiencing harm. Scholarly theses on robot intelligence, then, become sites on which definitions of intelligence and humanity rise to the fore. A review of these philosophical and ethical arguments grants insight into both a cyborg future and also, what (we seem to think) it means to be human more generally.

I can’t help but quote from the Japanese anime manga series, and live action film, Ghost in the Shell; “But that’s just it, that’s the only thing that makes me feel human. The way I’m treated. I mean, who knows what’s inside our heads? Have you ever seen your own brain?” This is Major Motoko Kusanagi speaking. She is a synthetic “full-body prosthesis” augmented-cybernetic human (Cyborg). The point Major Motoko Kusanagi raises is as important now as it has ever been, as humans consider a legal status for robots. How do humans tell if a robot, (or Cyborg) is truly intelligent, autonomous and in need of protection in the form of laws governing its existence?

Worzel argues that it is not possible to identify an ultimate breaking point between human and machine intelligence.  Worzel contends that at some point, robots and computers will be so complex that humans won’t be able to tell if they are truly intelligent or just simulating intelligence so convincingly that people cannot tell the difference.  To Worzel “a difference that makes no difference is no difference“. By this argument, if machines seem intelligent, then for all practical purposes they are intelligent. In this vein, others argue that human intelligence is predominantly related to environmental stimuli and only arbitrarily related to genetics. The people who make this argument contend that the brain is a very complex computing machine that is responding in a highly sophisticated but mechanical manner to environmental stimuli. If robots can only simulate intelligence, the argument goes, then so can we –it makes no difference if we are intelligent, or whether we just seem so. What seems to matter then is what Cyborg Major Motoko Kusanagi speaks, it is the way we’re treated.

Searle offers an opposing perspective—that which is simulated cannot also be real. At this point in time AI can only simulate the human brain and consciousness. That is, robotic intelligence is only capable of what Searle calls “weak AI”  (as opposed to “strong AI, in which machines possess the full range of human cognitive abilities, including self-awareness and sentience). Referring to non-sentient AI, Searle’s Weak AI Hypothesis states that robots—which run on digital computer programs—can have no conscious states, no mind, no subjective awareness, and no agency. Weak AI cannot experience the world qualitatively, and although they may exhibit seemingly intelligent behavior, it is forever limited by the presence of a “brain” but lack of a mind. For Searle, simulated consciousness is very different from the real thing, and AI cannot and should not compare and compete with our human understanding of consciousness.

However, Wallach and Allen suggest that a machine can be a genuine cause of harm amongst individuals and communities, indicating a distinct efficaciousness and a need for regulation. They argue that failure to behave within moral parameters among autonomous machines programmed to automate and regulate power grids, monitor financial transactions, make medical diagnoses and fight wars, could have devastating consequences. As machines become progressively more autonomous it may become increasingly necessary that robots should employ ethical subroutines to evaluate their possible actions before carrying them out. The more autonomous robots are, the less they are simple tools in the hands of other actors (such as the manufacturer, the operator, the owner, or the user, all of whom have the legal responsibilities so far). When attribution of harm cannot be traced back to a specific person or organization, significant legal and philosophical questions arise.

Figuring out the rights and responsibilities of intelligent robots entails explicit consideration of what intelligence means, what intelligence indicates, and what, if anything, separates humans from machines. Such considerations give rise to a central and longstanding question—what makes humans “human?”.  Perhaps what makes humans “human”, is how we are treated; perhaps what makes humans “human” is how we treat other beings; perhaps human intelligence, like machine intelligence, is mere simulation—a product of extrinsic shaping forces. Perhaps distinguishing “human” intelligence from “machine” intelligence will eventually lose meanings.  After all, “a difference that makes no difference is no difference” right?



Sebastian Trew holds a Master’s degree in Human Rights. His thesis considered the need to address the practice of intelligent robots and human rights for the safety of humanity. Sebastian is a PhD student at the Australian National University. His research is centered on robots and liability, rooted in sociological underpinnings.

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Making the world a better place has always been central to Mark Zuckerberg’s message. From community building to a long record of insistent authenticity, the goal of fostering a “best self” through meaningful connection underlies various iterations and evolutions of the Facebook project. In this light, the company’s recent move to deploy artificial intelligence towards suicide prevention continues the thread of altruistic objectives.

Last week, Facebook announced an automated suicide prevention system to supplement its existing user-reporting model. While previously, users could alert Facebook when they were worried about a friend, the new system uses algorithms to identify worrisome content. When a person is flagged, Facebook contacts that person and connects them with mental health resources.

Far from artificial, the intelligence that Facebook algorithmically constructs is meticulously designed to pick up on cultural cues of sadness and concern (e.g., friends asking ‘are you okay?’).  What Facebook’s done, is supplement personal intelligence with systematized intelligence, all based on a combination or personal biographies and cultural repositories. If it’s not immediately clear how you should feel about this new feature, that’s for good reason. Automated suicide prevention as an integral feature of the primordial social media platform brings up dense philosophical concerns at the nexus of mental health, privacy, and corporate responsibility. Although a blog post is hardly the place to solve such tightly packed issues, I do think we can unravel them through recent advances in affordances theory. But first, let’s lay out the tensions.  

It’s easy to pick apart Facebook’s new feature as shallow and worse yet, invasive and exploitative. Such dubiousness is fortified by a quick survey of all Facebook has to gain by systematizing suicide prevention. To be sure, integrating this new feature converges with the company’s financial interests in myriad ways, including branding, legal protection, and data collection.

Facebook’s identity is that of the caring company with the caring CEO.  Creating an infrastructure with which to care for troubled users thus resonates directly with the Facebook brand image. Legally, integrating suicide prevention into the platform creates a barrier against law suits. Even if suits are unlikely to be successful, they are nonetheless expensive, time-consuming, and of course, bad for branding. Finally, automated suicide prevention entails systematically collecting deeply personal data from users. Data is the product that Facebook sells, and the affective data mined through the suicide prevention program can be packaged as a tradeable good, all the while normalizing deeper data access and everyday surveillance. In these ways, human affect is valuable currency and human suffering is good for business.

At the same time, what if the system works? If Facebook saves just one life, the feature makes a compelling case for itself. A hard-line ideological protest about surveillance and control feels abstract and disingenuous in the face of a dead teenager. Moreover, as an integral part of daily life (especially in the U.S.), Facebook has taken on institutional status. With that kind of power also comes a degree of responsibility. As the platform through which people connect and share, Facebook could well be negligent to exclude safety measures for those whose sharing signals serious self-harm. If Facebook’s going to watch us anyway, shouldn’t we expect them to watch out for us, too?

A tension thus persists between capitalist exploitation through the most personal of means, the wellbeing of real people, and the social responsibility of a thriving corporate entity. Solving such tensions is neither desirable nor possible. These are conditions that exist together and are meaningful largely in their relation. A more productive approach entails clarifying the forces that animate these complex dynamics and laying out what is at stake. Recent conceptual work on affordances, explicating what affordances are and also, how they work, offers a useful scaffold for the latter project.

In an article published in the Journal of Computer Mediated Communication, Evans, Pearce, Vitak, and Treem distinguish between features, outcomes, and affordances. A feature is a property of an artefact (e.g., a video camera on a phone), an outcome is what happens with that feature (e.g., people capture live events) and an affordance is what mediates between the feature and the outcome (e.g., recordability).

Beginning with Evans et al.’s conceptual distinction, we can ask in the first instance:  What is the feature, what does it afford, and to what outcome?

The feature here is an algorithm that detects negative affect and evocations of network concern, and that connects concerning persons with friends and professional mental health resources. The feature affords affect-based monitoring. The outcome is multifaceted. One outcome is, hopefully, suicide prevention. The latent outcomes are relinquishment of more data by users and in turn, the acquisition of more user data by Facebook; normalization of surveillance; fodder for the Facebook brand; and protection for Facebook against legal action.

The next question is how automated suicide prevention affords affect-based monitoring, and for whom? Key to Evans et al.’s formulation is the assumption that affordances are variable, which means that the features of an object afford by degrees. The assumption of variability resonates with my own ongoing work[1] in which I emphasize not just what artefacts afford, but how they afford, and for whom. Focusing on variability, I note that artefacts request, demand, encourage, allow, and refuse.

Using the affordance variability model, we can say that the shift from personal reporting to automated reporting represents a shift in which intervention was allowed, but is now required for those expressing particular patterns of negative affect. By collecting affective data and using it to identify “troubled” people, Facebook demands that users get help, and refuses affective expression without systematic evaluation. In this way, Facebook demands that users provide affective data, which the company can use for both intervention and profit building. With all of that said, these requests, demands, requirements and allowances will operate in different ways for different users, including users who may strategically circumvent Facebook’s system. For instance, a user may turn the platform’s demand for their data into a request (a request which they rebuff) by using coded language, abstaining from affective expression, or flooding the system with discordant affective cues. What protects one user, then, may invade another; What controls me, may be controlled by you.

Ultimately, we live in a capitalist system and that system is exploitative. In the age of social media, capitalist venues for interaction exploit user data and trade in user privacy. How such trades operate, and to what effect, generate complex and often contradictory circumstances of philosophical, ideological, and practical import. The dynamics of self, health, and community as they intersect with the cold logics of market economy evade clear moral categorization. The proper response, from any subject position, thus remains ambiguous and uncertain. Emergent theoretical advancements, such as those in affordances theory, become important tools for traversing ambivalence—identifying the tensions, tracing how they operate, and setting out the stakes. Such tools get us outside of “good/bad” debates and into a place in which ambivalence is compulsory rather than problematic. With regard to suicide prevention via data, affordances theory lets us hold together the material realities of deep and broad data collection, market exploitation, corporate responsibility, and the value of saving human lives.


Jenny is on Twitter @Jenny_L_Davis

Note: special thanks to H.L. Starnes for starting this conversation on Facebook

[1] In a paper under review, I work with James Chouinard to explicate and expand this model.


Several nights ago, Uber saved my life prevented my becoming a distressed soul, lost and crying in a new country.  Had this event transpired to fruition, it would have been both emotionally exhausting and also, deeply troubled my  sense of self.  Luckily, however, I called an Uber, and here I am, nerves and feminist identity still well intact. In recounting the events of this banal and, in retrospect, marginally stressful experience, I’m reminded of the two nets that our devices weave: the trappings of dependence and the comfort of safety.

Here’s what happened: I was on a mission for fruit. Fruit not from a can. Fruit not dried into a nut bar. Fruit free from individual plastic wrapping. Real, Fresh, Fully Hydrated, Fruit. And so, on my second night in Australia, the land I now call home, I Google Mapped my way to an IGA X-Press. Armed with the cheapest “smart” phone I could purchase at the airport, I fumbled on foot down unfamiliar streets until, in what seemed more like an accident than a well followed plan, I found myself flesh to flesh with colorful and aromatic pears, apples, peaches, and citrus. I had arrived. With glee and pride I filled my cart with the fresh products that 30 hours of travel and temporary accommodation made scarce. I then slowly trecked down each aisle with anthropological interest in the breads, coffees, and packaged foods on offer. I chose Wallaby Bites to save for a late night treat, got thick ground coffee to use with my university-apartment-provided French press, marveled at all of the local dairy products, and felt strangely comforted by the familiar brands that I never bought in the U.S. and still wouldn’t buy here. I remained unwary of the weighty bags I would need to carry home, and unconcerned about the early signs of a setting sun.

Immediately upon leaving, I made a wrong turn. Actually, it may not have happened then. I’m still not sure when the first wrong turn happened, but I do know that one wrong turn dominoed into a series of wrong turns, so that I ended up on the side of a highway, and then somewhere on the Australian National University campus, and then back by the side of the highway again, in a different location. It was dark by then and my phone warned of 15% battery. Maps had long stopped being helpful. Perpetually searching for GPS, it was as though I had printed the original directions and carried with me a static piece of paper, like the old days when people used to Mapquest things.

I had become trapped by my dependence on an adaptive mapping system. My device would tell me where to go, I presumed, making wrong turns relatively benign. My phone would simply recalculate, and I would dutifully follow the pleasant roboticized voice. But this is not how things happened, and I realized I had been staring at my phone so intently, willing it to capture a signal, that I hadn’t paid close attention to my surroundings. I also hadn’t fully examined my route before setting out. I didn’t know where I was or the direction best to turn. In a city not designed on a grid system, and with sign structures and landmarks with which I was unfamiliar, the static map on my phone and the analog maps on the street left me struggling to translate curving and intersecting lines into my own location and that of my desired destination.

With the dark night in full bloom, I made an executive decision about how to allocate the remainder of my waning battery charge—I called an Uber. My knight in shining armor, a middle-aged man in a Kia Sport, drove me home. I was a couple miles away from my university apartment, and as we twisted through the city, I thought it was among the best $8.77(AUD) I had ever spent. We laughed as I told him what had happened, and, looking impressed, he said his wife would have been crying ages ago. I told him I was about 8% battery life away from that point.


Just as getting lost was a product of technologies’ net of dependence, the availability of a ride-share app empowered me to stay strong, providing a safety net when things didn’t go as planned. Though it was dark, and I was lost, and my grocery bag was leaving deep red imprints in the crook of my arm, I knew, the whole time, that I would be okay. I knew that I only needed to push a button, and a ride would come. If that didn’t work, I could push several buttons, and call a traditional cab, and again, a ride would come. I could mess up, (which I did) and have layers of contingency preventing my mishap from becoming a catastrophe.

The two nets that our technologies weave—that of dependence and safety—sit in both complement and tension with one another. As Nathan Ferguson says in his own lost-in-the-city account, these tools “reinforce a trust in a remote, arbitrary, comforting and pacifying, if no less sought after authority.” We come to need them, and also, to be empowered by them. We have a hand in their weaving and maintenance—waving off directions and electing to put in coordinates, while engaging in quick problem-solving when those coordinates fail, for example. We aren’t stupider because of our devices, but we do think differently, plan differently, and expect differently. We plan and expect to be adaptable, which is both a product and necessity of, the devices that we carry.

Today, I think I’ll go phone shopping. I hope I can find the mobile store.

Cyborgology Co-Editor Jenny L. Davis is a Soc. Prof. and an Aussie newbie. She is on Twitter @Jenny_L_Davis 

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headlineWhen talking about China, local digital media hypes are often temporalized on a yearly basis, resulting in a peculiar Chinese zodiac of tech-related buzzwords. 2005 was the Year of the Blog, 2008 The Year of Shanzhai, 2009 the Year of Weibo, 2012 the Year of WeChat, 2014 the Year of… well, it’s been the Year of WeChat for a few years now. Anyway, given the disproportionate attention being given to the phenomenon, 2016 is poised to be remembered as the Year of Livestreaming, or, as it is called in Mandarin Chinese, zhibo (literally ‘direct-casting’). The translation is revealing, because while livestreaming is commonly linked to videogaming and event broadcasting on platforms like Twitch (or, more recently, YouTube and Facebook) in Mainland China livestreaming is being adopted as a prominent content format by a wide variety of social media platforms, and has been enthusiastically embraced by users keen to share sights from their everyday lives, often through apps and websites that offer social networking capabilities, live commenting functions and microtransaction-based gifting.

I got in touch with my former colleague Dino Zhang to hear about his ongoing doctoral work at DERC (Digital Ethnography Research Center), and we exchanged a few thoughts around zhibo and content formats on Chinese digital media platforms. In 2014, Dino was kind enough to host me for the brief period in which our fieldworks overlapped in his home city of Wuhan, and we ended up writing some observations about Momo (perhaps 2014 was the Year of Dating Apps, who knows), a social contact app that was much touted as symptomatic of a Chinese “sexual revolution”, but that we instead found to be largely used for combating wuliao (boredom) through group chats and location-based social networking. Quite tellingly, two years later, Momo’s growing profits are fueled by its incorporation of a zhibo function which projects the platform further away from its narrow depiction as a “dating app” and typifies the shapeshifting nature of many local digital media platforms, forced by a competition for hundreds of millions of users to embrace and incorporate the latest functions and content formats.


1Gabriele de Seta: Your previous research project was about internet cafés in a second-tier Chinese city and the changes they went through during large-scale urban restructuring. You’ve also written about social contact apps and explored the concept of boredom in its relation with urban spaces. How did zhibo enter this picture?

Dino Zhang: I have been watching livestreams since 2013. I primarily used at the time and it was natural for me to begin taking some notes and building an archive of screenshots. Then in 2014 Chinese livestreaming platforms got my attention – Douyu was launched in 2014, followed by many other websites such as Panda TV, mobile platforms like Inke, existing apps relaunched as livestreaming platforms such as Momo, as well as numerous other minor competitors. There are several hundred livestreaming platforms operating in China today; the war for attention is fierce, and the hype is – at least commercially speaking – very real. But I don’t think this is the primary reason why I started doing research on livestreaming. In the past two years, the livestreaming industry in China has grown exponentially in terms of revenue and viewership, and has already mutated multiple times. Just take the example of Douyu: it originally started in 2013 as AcFun Namasho (生放送, livestreaming in Japanese), an integral part of the AcFun video sharing website, which was in itself an imitation of the Japanese platform Niconico. Then Acfun Namasho was relaunched in 2014 as Douyu TV, with a separate domain ( and an independent company behind it. The website was also entirely revamped after the basic style of while also retaining some of its distinctive core features such as the danmu (bullet barrage) commenting system, and a functional mobile app was also released. To put it simply, Douyu may have initially copied the basic digital infrastructure (web design, protocols, streaming technologies and so forth) of foreign platforms, but the later developments of the service have been primarily determined by the local Chinese context: emerging genres like huwai (outdoor livestreaming), user groups (many zhibo users live in the countryside rather than urban areas), user practices (streaming very mundane activities from ordinary spaces such as workplaces and homes), and aesthetic preferences (what sort of contents are considered fun or comfortable to watch). These peculiarities were what got me interested in Chinese livestreaming platforms in the first place.


2GdS: Has your research on zhibo changed your views about boredom and urban spaces?

DZ: My understanding of boredom was closely related to space, urban space to be precise. My previous research identified internet cafés as one example of this spatialized boredom. Despite the many shopping malls and entertainment complexes continuously popping up across Chinese cities, the young urban residents I interviewed evidenced how they still had very few options in terms of leisure spaces. Internet cafés, especially the ones that have been radically renovated in recent years, remain popular destinations, but livestreaming has offered me another perspective on boredom: temporality. Real time broadcasting provides a very comfortable sense of togetherness and security that Chinese audiences used to find in television. I am beginning to realize how, in terms of aesthetics, many Chinese livestreams do not resemble contemporary foreign platforms such as (which largely focus on the diversity of videogame playthroughs and the competitivity of e-sports) but rather livecam websites from the late 90s and early 2000s such as JenniCam. Yet, while lifecasting remained relatively at the margins of Euro-American livestreaming trends, in China very mundane daily activities have become the main content available on the majority of zhibo platforms. Besides the spectacles of e-sports and the occasional stunts of mainstream celebrities, tens of thousands of people are watching a barbecue vendor, a worker at a construction site, a sleeping girl, guinea pigs on treadmills, a woman eating animal entrails, a limbless person, surveillance camera footage of a building, a person wearing plastic bags walking on the street, and so forth. The mundanity of these zhibo is self-evident, and many of my informants end up asking themselves the same question: why are people watching these boring and meaningless zhibo?

3GdS: A recent article by Hao Wu states that both zhibo hosts and audiences don’t care about politics and that these platforms are merely breeding grounds for “endless banal entertainment”; according to the author, while many microblogging opinion leaders were older generations of better educated urbanites, the userbases of Chinese livestreaming platforms are made of diaosi (‘losers’ [sic]) who waste time and money on them to escape loneliness and hopelessness. In light of your work with streamers and audiences, do you think this characterization is accurate, and that zhibo reflects a further polarization between educated urban residents and uneducated, lonely rural diaosi (however problematic the term is)? Or are things more nuanced?

DZ: That article reflects the popular imagination of zhibo quite accurately— seen from the outside (often through only a few distracted glimpses), zhibo is mostly boring and meaningless, and is regularly disregarded as the lowest tier of Chinese cultural consumption; yet, many people who enter a zhibo channel with this prejudice still get hooked and go back to it regularly. Is it boring? If you look at zhibo generically, of course it seems absurd that anyone would be watching this sort of stuff regularly. But if you start engaging with individual users, the situation becomes way more nuanced. For example, I was talking to a livestreamer called Yuwen who is a disabled young man living in rural Sichuan. His life, according to most standards, is quite tragic. Despite the often abusive comments he receives in chat, Yuwen still carries on streaming because zhibo is an important opportunity for him to speak to a broader audience and receive some money through donations. Yuwen’s zhibo is extremely slow due the long pauses and interruptions resulting from his precarious Internet connection, the resolution of his webcam is very low and even his voice is barely heard over the microphone, yet he speaks in his own capacity and patiently responds to his viewers’ questions. The banality of zhibo contents can be a difficulty because genuine reflexive moments are buried by the duration itself – a six hour-long livestream may contain five minutes of extremely revealing and inspiring conversation about contemporary working life in the Chinese countryside, but only few people would be there to witness, record and publish them. How can we accuse livestreamers of producing “endless banal entertainment” if we have not yet tried to sit there and watch a six hour livestream in its entirety?


4GdS: I guess that this confirms how, like in many other media, genre and affect are central categories that one needs to keep in mind when trying to understand zhibo audiences. In the case of Yuwen, or of many other livestreamers from rural areas or marginal social strata, zhibo seems to be an important resource for finding human contact and sharing the predicaments of one’s everyday life. For others though, especially for the ones who command larger audiences and have turned themselves into livestreaming celebrities across multiple platforms, zhibo becomes a source of income, social capital, and potentially “media power” to use Castell’s term very broadly. Did you encounter examples that can highlight the different kinds of commercial and celebrity streamers?

DZ: Indeed, zhibo is an attention economy consisting of celebrities who rise and fall all the time. Streamers enjoy different levels of agency according to their individual situation. Some livestreamers have more autonomy while others are strictly controlled by third-party agencies. In terms of revenue, for example, Douyu and Bilibili provide a monthly stipend for livestreamers who are popular enough to be offered a contract with the platform. There are also different ways to generate income depending on what sorts of content you create: If you are predominantly a videogame livestreamer, besides the usual donations and platform stipend, you can obtain some income from external sponsors, and make extra money by selling your own merchandise (usually Taobao snacks) to your viewers. The main difference with platforms like, however, is how the cash flows. Douyu only allows donations via its own currency system, and strictly bans third-party systems like Alipay or PayPal. Conversely, many camgirls are hired by third-party agencies, so their salary is controlled by the agency rather than Douyu itself. This thriving informal industry is rather complicated and, according to unverifiable informal sources, a large part of Douyu’s revenue could be generated by the backroom deals between the website itself and these third-party agencies.


5GdS: Throughout your answers you emphasized how livestreaming challenges many presuppositions of digital ethnography (it requires synchronous participation rather than asynchronous, it is not automatically archived online, it is largely non-textual, interaction is one-to-many but audiences can respond through text, emojis, stickers, gifts, and so on). Could you outline your methodological approach to livestreaming and its challenges to the ideas of “field”, “participation”, and so on? This could be useful for other researchers getting into the topic.

DZ: I am not confident to say that my methods are entirely ethnographic because I improvised so much that I lost track of any central methodological principle. In the past two years, I have regularly watched many genres of zhibo, followed different sorts of streamers (zhubo) and interviewed some of them online and offline, hung out with viewers, attended several fan gatherings, monitored zhibo-related QQ groups, talked to people who do not watch or even hate livestreams, tried streaming myself on different platforms for more than 200 hours, used various software to archive streams and collect chat messages, and so forth. But out of all the things I have done, I think the foundation of my ‘field’ knowledge is built on my sustained efforts of watching zhibo. This daily work of spectating, archiving, and writing notes is the most frequent form of fieldwork I engage in. It sounds very straightforward, and perhaps a bit too casual, since it just involves sitting on in my armchair and viewing livestreams. The difficulty of this kind of research work lies in the endurance required by long-term observation. Every channel or livestreamer has its own particularities which do not necessarily coincide with the general impression you might gather from a cursory viewing of a highlights reel. As a zhibo channel grows, some practices peculiar to it might develop. For example, one livestreamer used to ban whoever donated money to him, and only accepted trolling as proper behavior in his channel – I could figure out the complex patterns of ritualized trolling only through regular observation and participation. Zhibo is very time-sensitive because of its live nature. Without subscribing to a fetishization of liveness, I still believe that the contextual information necessary to understand this sort of medium can be gathered only through long term ethnographic observation (complemented with Internet searches, forum browsing, fan interviewing, and so on). So, being there, watching zhibo and participating in the comment chat while events unfold, is crucial to the understanding of livestreaming.


Gabriele de Seta is a postdoctoral fellow at the Institute of Ethnology, Academia Sinica in Taipei, Taiwan. His research work, grounded on ethnographic engagement across multiple sites, focuses on digital media practices and vernacular creativity in contemporary China. He also experiments with ways of bridging anthropology and art practice. More information are available on his website

streamingdataFake news among the alt-right has been central in post-election public discourse, most recently instantiated through Donald Trump’s dubiously sourced tweet about the “millions of illegal voters” supposedly driving Clinton’s substantial lead in the popular vote. Less attention, however, has been paid to the way “real” news is, to use Jurgenson’s term, “fact-i”. Based in data and empirical accounts, mainstream news gets cast as respectable and objective vis-à-vis the fabrications and embellishments that go viral in right wing echo-chambers. This is especially true when journalists, stack of papers and obligatory pen studiously in hand, point to statistics that back up their reports.

Such reliance on, and valorization of, “data” masks the human underpinnings of journalistic practice and the ways that things become numbers and those numbers become stories. So here I present a cautionary tale of a small missing data point, with big narrative consequences.

It is a common truism that white male voters without college degrees disproportionately supported Trump in the 2016 election. Indeed, the notion that men with high school as their highest level of education were more likely to vote for Trump is an empirically supported fact. This data point spread widely throughout the campaign season, and bore out in the post-election analyses. But also in the post-election analyses, over which researchers pored in response to the statistically surprising result, another data point emerged that could have, but didn’t, change the narrative around this demographic voting bloc.

The data point that emerged was that white American men without college degrees have remained economically depressed since the 2008 recession and subsequent recovery. Although the U.S. economy has been steadily improving, the economic reality for this particular segment of the population has not. This is what Michael Moore talked about experientially (but not statistically), claiming that he knows the people who live in the rust belt, and they are struggling. He was right, the data show that they are struggling. Highlighting the economic reality for people without college degrees in the U.S. tells a very different story than highlighting the fact that they don’t have college degrees. The former renders an image of a voting contingent who, in the face of personal economic hardship that contrasts with national economic gain, are frustrated and eager to try something—anything—new. The latter renders an image of ignorance.

Data about education levels of voters is transformed by its coupling with economic trajectories. What’s been strange, is that although this coupling was discovered, it never really penetrated the larger “what happened” narrative. This is particularly strange given the meticulous and sometimes frantic search for explanation and the media’s public introspective quests to understand how so many got it all so wrong.

The transformative effect of the economic data point and its failure to effectively transform the story underlines two related things: data are not self-evident and narrative currents are hard to change.

The data weren’t wrong—people without college degrees were more likely to vote for Trump—but they were incomplete and in their partialness, quite misleading. That’s not a data problem, it’s a people problem. Data are not silent, but they are inarticulate. Data make noise, but people have to weave that noise into a story. The weaving process begins with survey construction, and culminates in analyses and reports. Far from an objective process, turning data into narrative entails nuanced decisions about the relevance of, and relationship between, quantifiable items captured through human-created measures. The data story is thus always value-laden and teeming with explicit and implicit assumptions.

Framing a contingent of Trump supporters through the exclusive metric of education without examining the interaction, mediating, and moderating effects of economic gains, was an intellectual decision bore out through statistical analyses. That is, pollsters, strategists, and commentators treated “lack of education” as the variable with key explanatory power. Other characteristics or experiences of those with low levels of education could/should/would be irrelevant.

Such dismissal created a major problem with regard to Democratic strategy. To situate a voting bloc as “uneducated” is to dismiss that voting bloc. How does one campaign to those voting in ignorance? In contrast, to situate a voting bloc as connected through an economic plight not only validates their position, but also gives a clear policy platform on which to speak.

But okay, after the election, analysts briefly shed light on the way that economics and education operated together to predict candidate preference. Why has this gotten so little attention? Why is education—rather than economics or the economic-education combination—still the predominant story?

The predominance of education level remains because narrative currents are strong. Even when tied to newly emergent data, established stories are resistant to change. Narratives are embedded with social frameworks, and changing the story entails changing the view of reality. A key tenet of sociology is that people tend towards stability. Once they understand and engage the world in a particular way, they do social and psychological gymnastics to continue understanding and engaging the world in that way. To reframe (some) Trump voters as part of an economic interest group that has been recently underserved, is an upheaval of previous logics. Moreover, disrupting existing logics in this way forces those who practice those logics to, perhaps, reframe themselves, and do so in a way that is not entirely flattering or identity affirming. To switch from a frame of ignorance to a frame of economics is to acknowledge not only that the first frame was distorted, but also, to acknowledge that getting it wrong necessarily entailed ignoring the economic inequality that progressives take pride in caring so much about. Switching from ignorance to economics entails both a change in logic and also, a threat to sense of self.

Data are rich material from which stories are formed, and they are not objective. Tracing data is a process of deconstructing the stories that make up our truths—how those stories take shape, evolve, and solidify into fact. The “truth” about Trump voters is of course complex and highly variable. The perpetually missed nuances tell as much of a story as those on which predominant narratives hang.


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Jenny Davis is on Twitter @Jenny_L_Davis


Editor’s Note: This essay originally ran on November 9, 2016 and included a call to politics of affinity. On November 10th, I added to the essay by applying the framework to ongoing protests. 

As the reality of the 2016 election results sunk in, my echo-chamber of a leftist newsfeed was full of two key things: heartbreak and I told you so’s. The heartbroken expressed disbelief that the U.S. would elect a person with an impressive record of bigotry coupled with an appalling record of incompetence. The I told you so’s said they already knew. Not knowing was a sign of privilege, naivety, foolish trust in big data. We should have nominated Bernie, they said. You should have voted, but not for Jill Stein.

Donna Haraway, so keen on blurring boundaries, promotes what she calls affinity politics, vis-à-vis identity politics. Identity politics mobilize around identity labels and the interests associated therein. Affinity politics intersect identities that share the same general agendas. Affinity politics circumvent identity boundaries and conjoin those who dream and work for similar causes. From Haraway’s  Cyborg Manifesto:

Identities seem contradictory, partial, and strategic. With the hard-won recognition of their social and historical constitution, gender, race, and class cannot provide the basis for belief in ‘essential’ unity…

The recent history for much of the US left and US feminism has been a response to this kind of crisis by endless splitting and searches for a new essential unity. But there has also been a growing recognition of another response through coalition — affinity, not identity

The I told you so’s represent identity politics, but so too do some of the heartbroken. In this moment of microcelebrity and performative social media, we are both people and brands. Politics, though always connected to sense of self, becomes a high stakes marker when sharing and posting are both expected and always up for comment and critique.

Today’s critical leftism is about being smart, owning the sharpest and most unexpected take, creating self-distinction and in so doing, creating fissures among those who grapple after the progressive label—fissures between pragmatists and hard-liners, anarchists and party members, collaborators and confrontationists. Identity distinction serves those who tack such distinction to themselves, but aren’t effective in the business of doing. And as is now spectacularly clear, the business of doing is serious.

Understanding the U.S. (and global) hard rightwing pushback makes for a complex puzzle. But let’s start with ourselves, the progressive left. What did we do and how can we do better? Politics of identity are a tangible culprit. The palpable elitism cited by those on the right is not off base. We’re snarky, and self-satisfied, and so caught up in “getting it” that we engage in esoteric conversations of relevance only to ourselves. For those who don’t understand, or who disagree, or who feel ridiculed and left out, Donald Trump is a validating force.

If we make it less about who we are and more about what we need to do, could we approach the business of doing, differently? If we root our movements in politics of affinity, might we recognize that our goals are the same even if the means and the tools might be quite different? I think so. Because affinity politics are animated less by ego and more by shared goals. If we begin at the hoped for end—obtaining national healthcare, ending the police state and its sharp effects within communities of color, replenishing environmental resources, distributing wealth in ways that are both equitable and humane, disconnecting moneyed elites from political elites, establishing a standard of global diplomacy, preserving women’s reproductive rights, and insisting upon safety and full inclusion for LGBQT* persons—we can perhaps have more sober discussions and flexible positions on how best to get there.

So what does affinity politics look like? It looks like meeting those who share similar goals where they are, appreciating their positions and their courses of action, and figuring out how to incorporate those positions and those actions into the tangible change that we all want. It means offering gentle critique and remaining humble and open to those who challenge your perspective. It means remaining firm and also, pliable.

Lest I deal in abstractions, let’s go now to a concerete case: the post-election protests.  Presented in generalities, those protesting represent radical leftism with goals of upturning existing structures. Progressives who oppose the protests represent a more moderate position that maintains value in the democratic system. The latter is a pragmatist approach to change from within. “Let’s be reasonable,” the pragmatists say, while the radicals claim that the time for reason has past. Okay. But we need to do something, so let’s figure it out.

Each of these are valuable positions and important tactics. Both of these groups share the goals of equality and inclusion. Neither group’s positions or strategies negate the other’s. Let’s think about how we can reconcile these divergent logics in a productive way.

My proposal, subject to the tweaks and critiques of memeification in its most collaborative form, is to maintain the protests but reframe them symbolically and tie their symbolism to action items.

Call it a demonstration and/or a unity march instead of a protest.

What’s so valuable about a gathering like this is the symbolism of strength against oppressive powers. The demonstrations across the country make clear that although our electoral system produced a right wing president, that decision far from reflects the sentiment of all the people. This symbolism can be a key source of strength for all of us, but especially those who have been harshly cast into the role of target. A unifying show doesn’t need specific demands. It doesn’t need to protest something. It is instead a demonstration of strength and caring that communicates a powerful message: We are here and we are together and we are ready to get to work.

Insist on accountability instead of calling for obstruction.

Michael Moore’s day after to-do list includes a call to obstruct all legislative action in ways that mirror Obama’s experiences with conservative lawmakers. This sentiment can be remolded into accountability. Rather than preemptively stopping everything (a distinctly political move), we can construct positions on actual policy proposals once we know their content. It is far more effective to make specific demands upon specific legislative documents. Doing so creates an opportunity to collaborate across political identities (even conservative ones) in ways that keep end goals at the center. Plus, maybe Trump will propose something good. I could get behind congressional term limits and would hate to already commit to opposition.

Draft a list of legislative priorities and link them to existing and potential lawmakers who would enact these policies. Support those politicians.

What do we care about and how can we make those things happen? Which senators and representatives support bolstering the ACA? Who has expressed support for Black Lives Matter? Who wants to raise the minimum wage? Bernie Sanders and Elizabeth Warren are obvious allies, but others are too. Kai Degner just lost in my district, but he’s pro-union, pro-LGBQT*, active in campaign finance reform, and an environmental protectionist. I’m certain we can identify others like Degner at the local and state levels and work to lift them up.

Draft a list of legislative redlines and link them to existing and potential lawmakers who would enact these policies. Push back against those politicians and support their adversaries in upcoming elections.

What are we most worried about and who do we think will put those worries into action? Who fought the hardest against marriage equality? Who wants less regulation? Who is adamant about law and order? Mitch McConnell, Sarah Palin, and Rudy Giuliani are known culprits, along with the lesser knowns like Bob Goodlatte, who beat Degner in my district. Just as we lift up those who share progressive values, we can take down those who traffic in oppression.



*Special thanks to James Chouinard who should probably have shared authorship and was especially helpful thinking through leftist fissures and their tangible consequences. And special thanks to the whole Cyborgology team, whose thoughtful discussion and debate helped me formulate the second half of this essay.

Jenny Davis is on Twitter @Jenny_L_Davis

Headline Pic Via: Source

A substantial part of my graduate research work focused on the vernacular creativity of Chinese digital media users. In practical terms, this meant participating in various local social media platforms and collecting content that my contacts shared through chat applications and posted on their personal social media feeds. Given that most of my friends and acquaintances knew I was doing research about 网络文化 wangluo wenhua [Internet culture], it wasn’t uncommon to receive proactive updates about newly-minted slang terms or hot-button funny images of the week, often accompanied by detailed explanations and personal interpretations of the content in question. Sometime in 2014, right at the beginning of my actual fieldwork, a friend from Shanghai sent me a stylized image of a frog with teary eyes and pouty lips on the popular chat application QQ. “What is this?” I asked. “It’s 伤心青蛙 shangxin qingwa [sad frog],” he replied. “I see… but do you know where it comes from?” I continued. “Hahaha, no, I don’t… it’s just funny, it’s really popular now on the Baidu Tieba forums, I got it there. There’s many versions of it.”

“I’m so sad I mutated”, one of the Pepe images I collected on Chinese social media platforms.
“I’m so sad I mutated”, one of the Pepe images I collected on Chinese social media platforms.

In fact, I knew that the vaguely humanoid frog was Pepe, a character originally appearing in Matt Furie’s Boy’s Club comic series that had by that time already become an archetypal figure of American digital folklore, circulating from relatively unknown bodybuilding forums to massive discussion boards like 4chan and Reddit, and mutating from his trademark “feels good man” comic panel into an endless series of self-referential variations and meta-ironic phenomena such as rare pepes. The fortuitous and unpredictable popularity of Pepe, rising from one among many characters of an independent comic to paragon “Internet meme”, has been amply chronicled as one of the most evident examples of how the creative practices of digital media users can near-instantly put anyone or anything under the spotlight of “Internet fame”. Matt Furie himself, reflecting on the unexpected rise to fame of one of his artistic creations, describes the cultural dynamics evidenced by the circulation of Pepe in terms of “post-capitalist” vernacular creativity: “It’s like a decentralized folk art, with people taking it, doing their own thing with it, and then capitalizing on it using bumper stickers or t-shirts.”

Despite the global reach of its iconicity, the history of Pepe – from its origins in independent comics to its “going mainstream” on the social media accounts of celebrities like Nicky Minaj or Katy Perry – is for the most part narrated as a thoroughly American story. Most recently, the archetypal chill-frog has experienced a further bout of popularity after being adopted as a humor device by Donald Trump supporters across multiple online platforms, subsequently identified by the Hillary Clinton electoral campaign as “a symbol associated with white supremacy” and eventually condemned by the Anti-Defamation League as an “anti-semitic symbol”.  Interpellated again regarding the latest problematic re-appropriations of his iconic character turning into a “culturally thick object”, Matt Furie has minimized the phenomenon as “just a product of the internet.” Yet, years before his mainstream popularity and politicized re-appropriations, Pepe had already made it to Chinese social media with surprising results.

At the beginning of my research on vernacular social media content in China, commonplace idealizations regarding “the Chinese Internet” – often imagined as an exotic cyberspace sealed off by the Great Firewall – had led me to expect a neatly separated local repertoire of vernacular content. But as often happens, engaging directly with the circulation of digital folklore results in unexpected insights. Indeed, protectionist policies, censorship mechanisms and the governmental clutch on the development of Chinese Internet industries have evidently resulted in clearly separated technical and economic infrastructures, yet the existence of a self-contained “Chinese internet” of vernacular content is much less evident. Along with repertoires of local QQ emoticons, TV series animated GIFs and Jiang Zemin antics, user interactions on Chinese social media platforms also make use of content sourced from more global repertoires such as Rage Comics, Japanese anime characters, Doge the Shiba Inu dog and Wojak the Feels Guy. During my data collection, I started to file this sort of content under the tag “transnational,” and Pepe is perhaps the single most striking example of the transnational circulation of digital folklore.

Series of Mandarin-captioned sad frog biaoqing collected on the microblogging platform Sina Weibo.
Series of Mandarin-captioned sad frog biaoqing collected on the microblogging platform Sina Weibo.

Friends who introduce Pepe to me during QQ conversations call him shangxin qingwa, or sad frog. When I ask them why they like him or enjoy using his pictures in chat messages, they reply that he is weird, funny, and they can empathize with his existential sadness. Multiple local versions of shangxin qingwa, augmented with Mandarin captions, accumulate over the years in my database of Chinese digital folklore. Pepe becomes a sad frog crossing local genres of vernacular content, from pixelated screen-captures shared on QQ and edited on-the-fly to more codified 表情 biaoqing [literally ‘expressions’, a wide category including emoticons, reaction images and stickers] popular on WeChat and collected in variegated 表情包 biaoqing bao [expression packs] ready for use on chat programs and apps. Pepe has made it to China as a sad frog, and sits snugly in personalized sticker menus, reaction image folders and biaoqing repositories along with political figures, Korean celebrities and local social media mascotte Tuzki the rabbit.

Besides its popularity as a semiotic resource, the sad frog phenomenon is also extensively discussed across social media posts and articles. A Douban post by Shi Yezhong chronicles the online circulation of frogs from the Crazy Frog song and Kermit the Frog captioned GIFs to the Foul Bachelorette Frog advice animal and Pepe himself. Yet it is the comment section that interestingly reclaims a local frog heritage, with other Douban users suggesting that 蛤 ha [‘toad’, a humorous nickname for ex-president Jiang Zemin] should be included in the list as a “Chinese mutation” wearing the leader’s iconic high-belt trousers and thick glasses. One thread on the Q&A website Zhihu titled “Why did sad frog become so popular?” receives a detailed answer by a user recounting of an intensive three-day exposure to sad frog biaoqing in a WeChat group chat: “there were more than 1,000 new messages every day, and this girl surprisingly kept participating in all discussions without sending any text or voice message, she! just! used! sad! frog! expressions!”. A few days later, another girl from the same WeChat group started drawing sad frog profile pictures caricatures of all group members, transforming the character into an intimate creative device. Notwithstanding his popularity across Chinese social media platforms, some local explainers blame most users for not understanding Pepe and not respecting his origins: “filenames like ‘World’s Saddest Frog biaoqingbao’ are just too stupid – if Matt Furie ever saw them, he would cry”.

Personalized sad frog profile pictures drawn by a WeChat group member. Source: Zhihu
Personalized sad frog profile pictures drawn by a WeChat group member. Source: Zhihu

As expected in light of the pervasive commercial aspect of digital media in China, vernacular creativity doesn’t stop at co-produced emoticons and profile picture drawings. The Rule 34 of the Chinese Internet could read: “There’s nothing you can’t find on Taobao”, and Pepe is a case in point. A simple search for shangxin qingwa on the e-commerce behemoth results in a wide variety of sad frog merchandise, from WeChat sticker packs (¥1.98) and smartphone covers (¥26.90) to frog eyes sleeping masks (15.50¥) and Pepe-head tissue dispensers (¥35.00). The description of another product – a sad frog handwarmer pillow – provides an constellation of terms useful to understand the context of this sort of merchandise: ACG [animation, comics & games], QQ biaoqing, and 情精神污 jingshen wuran [‘spiritual pollution’, an ironic term for obsessive online phenomena]. As shangxin qingwa, Pepe has entered a vast pantheon of characters drawn from the universes of ACG fandom, found spaces in the customizable features of social media platforms, and is being profited off as a popular ‘spiritually polluting’ phenomenon. Matt Furie has declaredly been collecting artisanal Pepe pins, t-shirts and earrings sold on websites like Etsy, and has even launched a Pepe Official clothing line, but has probably no idea of the degree to which his character is being commercialized on industrial scale in China.


 Some of the shangxin qingwa merchandise sold on Taobao, China’s largest online trading website.

Some of the shangxin qingwa merchandise sold on Taobao, China’s largest online trading website.

Where does all of this leave us? Matt Furie’s insights on the fortuitous career of his own character seem more relevant than ever: just like in many other places and through many other media, Chinese users are taking Pepe and “doing their own thing with it” – being it expressing their existential sadness through a QQ emoticon, compiling sticker packs to share with friends, drawing a caricature of WeChat group members or mass-producing frog-shaped tissue dispensers. In China, he is shangxin qingwa, a sad frog, one of the many characters belonging to the ever-growing pantheon of tongue-in-cheek ‘spiritually polluting’ content, accompanying digital media users all the way from their chat conversations to their smartphone covers. More generally, Pepe’s Chinese career offers a new perspective on “Internet memes”, a genre of vernacular content which is all-too-often described through the debatable vocabulary of memetics and interpreted through predominantly Euro-American cultural politics. The social life of sad frogs, along with that of many other examples of transnational digital folklore, invites to consider other parameters (funniness, expressivity, guilty pleasure), practices (interpreting, translating, explaining) and dynamics (circulation, collection, commercialization) in order to move the study of locally constructed genres of vernacular content such as biaoqing and jingshen wuran beyond the moral politics and diffusionist explanations of our memetic obsessions.

Gabriele de Seta is a postdoctoral fellow at the Institute of Ethnology, Academia Sinica in Taipei, Taiwan. His research work, grounded on ethnographic engagement across multiple sites, focuses on digital media practices and vernacular creativity in contemporary China. He also experiments with ways of bridging anthropology and art practice. More information are available on his website


Pundits across the political spectrum have expressed outrage at Trump’s continued insistence that the presidential election is rigged, and seem quite scandalized at his stated unwillingness to agree, apriori, to accept the final results.  Trump’s critics argue that his distrust of the election process threatens to destabilize U.S. democracy by undermining the ideology of citizen-driven governance. It is horrifying they say, and more than that, his claims are dangerous.

While a smooth transition of power is indeed a hallmark of democracy, there is a distinct disingenuousness about the breathless moralizing against Trump’s claims. It’s hard to ignore the sharp dissonance that emerges when broadcast journalists report on the economics of campaign finance, the political collusion and corruption revealed through an email leak, and then, without even the interruption of a commercial break, turn to Camera 2 and condemn Donald Trump for questioning the integrity of the democratic process.  

A true representative democracy is derived entirely from the expressed needs and wishes of the electorate. I don’t imagine many people believe—or ever believed—that the U.S. practices democracy in such pristine form (the very existence of private campaign financing, under any sort of regulatory policy arrangement, automatically disavows the notion of a true meritocratic and voter-driven system). In practice, all systems of government are versions of themselves. They encompass the spirit of the ideology, rather than the rule.  Governing bodies are not, to use a Weberian term, “ideal types” of the ideological system that they represent.

The distortion of democracy is an open secret among the populace. Citizens know, or at least sense, that governing bodies are selected by, and in the service of, elite networks over which voters themselves have little control. This is reflected in truisms about the fate of third-party candidates, whose primary relevance is their fractional vote siphoning from democrats and republicans; it’s how you know, and I know, that nobody we know, could ever run for national office. So why get bent out of shape when a presidential candidate calls the democratic process into question? The answer is twofold. First, Trump’s brazen and explicit mistrust of the process undermines the ritual of a democratic system. Second, Trump misunderstands how the system is rigged, and thus makes unsubstantiated claims that are both incendiary and also, easily refuted.

Erving Goffman’s theory of ritual interaction is instructive in understanding the backlash against Trump’s claims of a rigged election. Goffman theorizes that human interaction is fragile. Each interaction entails the possibility of a misstep, causing embarrassment for all involved and dissolving the shared definition of the situation. Goffman says that people work collaboratively to maintain smooth interaction in the face of threats such as bodily emissions, misspoken comments, interruptions, distractions, etc. A key tool in maintaining smooth interaction is what Goffman calls tact, or civil inattention. This is the practice of actively ignoring, as long as possible, those missteps in others that would cause the interaction to break down. Concretely, this means diligently avoiding the spinach in someone’s teeth; it means intentionally mispronouncing a word that one’s interaction partner mispronounces so as not to call attention to the mistake; it means covertly inserting one’s own name into conversation to compensate for, but not call out, another who seems to have forgotten it.

As a system of human interaction, democracy too, is fragile. It is vulnerable to its own imperfections and requires elaborate rituals to maintain ideological integrity, including civil inattention. Claims of a rigged election are not a lie that dishonors an otherwise pure democratic system, but rather, an impolite truth that disrupts the ritual interaction by which democratic ideology is maintained. In short, Trump’s grievances against the democratic process represent a failure of tact.

Refusing to engage in tact at a societal level is an important political tool. #BlackLivesMatter, #OccupyWallStreet, and the civil rights movement are all examples of factions who did away with tactful inattention and instead, disrupted economic and political institutions that systemically exclude and marginalize entire groups of people. In this way, a tactless call-out of the democratic process itself is both healthy and, with the conditions of a digitally mediated social structure, increasingly inevitable. Even Goffman says that tact has its limits, and this election cycle, those limits have been pushed.

In the contemporary U.S., divergences between political convention and the ideological spirit of democracy have become blaring. The use of electronic and digital communication tools means that political, business, and media elites document their interactions and negotiations. These exchanges are vulnerable to hacks and leaks, and substantiate the kinds of arrangements that many Americans felt but couldn’t directly point to. These documents and their circulation in a 24hr news cycle bring the inner-workings of the political sausage factory more plainly into public view. Tactlessly calling elite actors to account and pushing the democratic system to adhere to its principles is a laudable response.

And yet, Trump remains indefensible, or at least ineffective.  Trump and his surrogates engage tactlessly towards democratic practice, but they misarticulate how the election process is corrupt. In doing so, they undermine the potential for real, tough conversations about who benefits from existing political arrangements.

Trump’s claims of a rigged election are based on supposed widespread voter fraud. Trump’s campaign cites dead people, fake people, and non-citizens who are on voter rosters. But these claims are simply not substantiated.   Neither the deceased—nor those impersonating them—will show up to the polls on November 8th. Trump tacks his claims of corruption to the practice of voter fraud likely because this makes for a more digestible message than interrogating the complex and nebulous ways that political, media, and economic elites swing in the same circles, think in similar ways, and serve each other’s interests with the tools at their respective disposals. Democratic corruption is more ambient and diffuse than the hand-wringing conspiracy that voter fraud represents. But Trump and his campaign leverage claims of corruption to discredit a system in which he now finds himself on the losing end. For such purposes, simple messaging is perhaps of greater value than precision.  And so Trump’s tactless message bounces off of the political system, easily dismissed for its inaccuracy without compelling any real change. And that’s a shame.

It’s a shame because this election—and the political system more generally—is absolutely rigged, but not because of voter fraud. It is rigged in the sense that larger mechanisms are at play than individual voter decisions. By the time a voter steps into the voting booth, the terms of the election are already set, the choices already winnowed down so that no matter what box voters check, power-elites remain intact. This doesn’t mean that democracy is a farce or that transitions of power should be violent. It does mean that we should have frank discussions about the real workings of what we call democracy. And more than ever, the public is poised to push such conversations. We have the many-to-many communication tools, the capacity to self-publish, the capacity to surveil figures of authority, and we have access to political documents never meant for citizens’ eyes. We are in a position to refuse political tact, as long as we get the critique of democracy right.

Any system worth its salt should be robust enough to absorb a tactless challenge, maintaining integrity even as weak spots are identified and holes poked through. Refusing tact can indeed be an important way of shoring up and sharpening a political system. It is not an overthrow, but a harsh audit; rudely but effectively, and lovingly, drawing attention to the spinach in America’s teeth.


Jenny Davis is on Twitter @Jenny_L_Davis

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