social media | Digifesto

May 6, 2020

Considering “Neither Hayek nor Habermas”

I recently came upon an article from 2007, Cass Sunstein’s “Neither Hayek nor Habermas”, arguing that “the blogosphere” would have neither as an effective way of gathering knowledge or as a field for consensus-building. There is no price mechanism, so Hayekian principles do not apply. And there is polarization and what would later be called “echo chambers” to prevent real deliberation.

In an era where online “misinformation” is a household concern, this political analysis seems quite prescient. There never was much reason to expect free digital speech to amount to much besides a warped mirror of the public’s preexisting biases.

A problem with both Hayekian and Habermasian theory, when used this way, is the lack of institutional specificity. The free Web is a plurality of interconnected institutions, with content and traffic flowing constantly between differently designed sociotechnical properties. It is an naivete of all forms of liberal thought that useful social structure will arise spontaneously from the interaction between individuals as though through some magnetic force. Rather, social structures precede and condition the very possibility of personhood and discourse in the first place. “Anyone who says differently is selling something.”

Indeed, despite all the noise on the Internet, there are Hayekian accumulations of information wherever there is the institution of the market. One reason why Amazon has become such a compelling force is because of its effective harnessing of reviews on products. Free speech on the Internet has been just fine for the market.

What about for democracy?

If free digital speech has failed to result in valuable political deliberation, it is wrong to fault the social media platforms. Habermas expected that money and power will distort public discourse; a privately-owned social media platform is a manifestation of this distortion. The locus of valuable political deliberation, therefore, must be in specialized public institutions: most notably, those institutions dedicated to legislation and regulation. In other words, it is the legal system that is, at its best, the site of Habermasian discourse. Not Twitter.

If misinformation on the Internet is “a threat to our democracy”, the problem cannot be solved by changing the content moderation policies on commercial social media platforms. The problem can only be solved by fixing those institutions of public relevance where people’s speech acts matter for public policy.

The closest thing to such a Habermasian institution in the Internet today is perhaps the Request for Comments process on adminstrative regulations in the U.S. There, citizens can freely express their policy ideas and those ideas are, when the system is working, moderated and channeled into nuanced changes to policy.

This somewhat obscure and technocratic government function is overshadowed and sometimes overturned by electoral politics in the U.S., which are at this point anything but deliberative. For various reasons concerning the design of electoral and legislative institutions in the U.S., politics is only superficially discursive. It is in fact a power play, a competition over rents. Under such conditions, we would expect “misinformation” to thrive, because public opinion is mostly inconsequential. There is nothing, pragmatically, to incentivize and ground the hard work of deliberation.

It is perhaps interesting to imagine what kind of self-governing institution would deserve this kind of investment of deliberation.

References

Benthall, Sebastian. “Designing networked publics for communicative action.” Interface 1.1 (2015): 3.

Bruns, Axel. “It’s not the technology, stupid: How the ‘Echo Chamber’and ‘Filter Bubble’metaphors have failed us.” (2019).

Sunstein, Cass R. “Neither Hayek nor Habermas.” Public Choice 134.1-2 (2008): 87-95.

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August 7, 2018

Racial projects and racism (Omi and Winant, 2014; Jeong case study)

Following up on earlier posts on Omi and Winant, I’ve gotten to the part where they discuss racial projects and racism.

Because I use Twitter, I have not been able to avoid the discussion of Sarah Jeong’s tweets. I think it provides a useful case study in Omi and Winant’s terminology. I am not a journalist or particularly with-it person, so I have encountered this media event mainly through articles about it. Here are some.

N.B. Sep. 17 2020 – These informal notes were part of the process of writing “Racial categories in machine learning”, with Bruce Haynes.

To recap, for Omi and Winant, race is a “master category” of social organization, but nevertheless one that is unstable and politically contested. The continuity of racial classification is due to a historical, mutually reinforcing process that includes both social structures that control the distribution of resources and social meanings and identities that have been acquired by properties of people’s bodies. The fact that race is sustained through this historical and semiotically rich structuration (to adopt a term from Giddens), means that

“To identify an individual or group racially is to locate them within a socially and historically demarcated set of demographic and cultural boundaries, state activities, “life-chances”, and tropes of identity/difference/(in)equality.

“We cannot understand how racial representations set up patterns of residential segregation, for example, without considering how segregation reciprocally shapes and reinforces the meaning of race itself.”

This is totally plausible. Identifying the way that racial classification depends on a relationship between meaning and social structure opens the possibility of human political agency in the (re)definition of race. Omi and Winant’s term for these racial acts is racial projects.

A racial project is simultaneously an interpretation, representation, or explanation of racial identities and meanings, and an effort to organize and distribute resources (economic, political, cultural) along particular racial lines.

… Racial projects connect the meaning of race in discourse and ideology with the way that social structures are racially organized.

“Racial project” is a broad category that can include both large state and institutional interventions and individual actions, “even the decision to wear dreadlocks”. What makes them racial projects is how they reflect and respond to broader patterns of race, whether to reproduce it or to subvert it. Prevailing stereotypes are one of the main ways we can “read” the racial meanings of society, and so the perpetuation of subversion of stereotypes is a form of “racial project”. Racial projects are often in contest with each other; the racial formation process is the interaction and accumulation of these projects.

“Racial project” is a useful category partly because it is key to Omi and Winant’s definition of racism. They acknowledge that the term itself is subject to “enormous debate”, at times inflated to be meaningless and at other times deflated to be too narrow. They believe the definition of racism as “racial hate” is too narrow, though it has gain legal traction as a category, as in when “hate crimes” are considered an offense with enhanced sentencing, or universities institute codes against “hate speech”. I’ve read “racial animus” as another term that means something similar, though perhaps more subtle, than “racial hate”.

The narrow definition of racism as racial hate is rejected due to an argument O&W attribute to David Theo Goldberg (1997), which is that by narrowly focusing on “crimes of passion” (I would gloss this more broadly to “psychological states”), the interpretation of racism misses the ideologies, policies, and practices that “normalize and reproduce racial inequality and domination”. In other words, an adequate use of racism, as a term, has to reference the social structure that is race.

Omi and Winant define racism thus:

A racial project can be defined as racist if it creates or reproduces structures of domination based on racial significance and identities.

A key implication of their argument is that not all racial projects are racist. Recall that Omi and Winant are very critical of colorblindness as (they allege) a political hegemony. They want to make room for racial solidarity and agency despite the hierarchical nature of race as a social fact. This allows them to answer two important questions.

Are there anti-racist projects? Yes. “[W]e define anti-racist projects as those that undo or resist structures of domination based on racial significations and identities.”

Note that the two definitions are not exactly parallel in construction. To “create and reproduce structure” is not entirely the opposite of “undo or resist structure”. Given O&W’s ontology, and the fact that racial structure is always the accumulation of a long history of racial projects, projects that have been performed by (bluntly) both the right and the left, and given that social structure is not homogeneous across location (consider how race is different in the United States and in Brazil, or different in New York City and in Dallas), and given that an act of resistance is also an act of creation, implicitly, one could easily get confused trying to apply these definitions. The key word, “domination”, is not defined precisely, and everything hinges on this. It’s clear from the writing that Omi and Winant subscribe to the “left” view of how racial domination works; this orients their definition of racism concretely. But they also note that the political agency of people of color in the United States over the past hundred years or so has gained them political power. Isn’t the key to being racist having power? This leads O&W to the second question, which is:

Can Group of Color Advance Racist Projects? O&W’s answer is, yes, they can. There are exceptions to the hierarchy of white supremacy, and in these exceptions there can be racial conflicts where a group of color is racist. Their example is in cases where blacks and Latinos are in contest over resources. O&W do not go so far as to say that it is possible to be racist against white people, because they believe all racial relations are shaped by the overarching power of white supremacy.

Case Study: Jeong’s tweets

That is the setup. So what about Sarah Jeong? Well, she wrote some tweets mocking white people, and specifically white men, in 2014, which was by the way the heyday of obscene group conflict on Twitter. That was the year of Gamergate. A whole year of tweets that are probably best forgotten. She compared white people to goblins, she compared them the dogs. She said she wished ill on white men. As has been pointed out, if any other group besides white men were talked about, her tweets would be seen as undeniably racist, etc. They are, truth be told, similar rhetorically to the kinds of tweets that the left media have been so appalled at for some time.

They have surfaced again because Jeong was hired by the New York Times, and right wing activists (or maybe just trolls, I’m a little unclear about which) surfaced the old tweets. In the political climate of 2018, when Internet racism feels like it’s gotten terribly real, these struck a chord and triggered some reflection.

What should we make of these tweets, in light of racial formation theory?

First, we should acknowledge that the New York Times has some really great lawyers working for it (Jeong herself having a law degree). Their statement was that at the time of the tweets, (a) Jeong was being harassed, (b) that she responded to them in the same rhetorical manner of the harassment, that (c) that’s regrettable, but also, it’s long past and not so bad. Sarah Jeong’s own statement makes this point, acknowledges that the tweets may be hurtful out of context, and that she didn’t mean them the way others could take them. “Harassment” is actually a relatively neutral term; you can harass somebody, legally speaking, on the basis of their race without invoking a reaction from anti-racist sociologists. This is all perfectly sensible, IMO, and the case is pretty much closed.

But that’s not where the discussion on the Internet ended. Why? Because the online media is where the contest of racial formation is happening.

We can ask: Were Sarah Jeong’s tweets a racial project? The answer seems to be, yes, they were. It was a representation of racial identity (whiteness) “to organize and distribute resources (economic, political, cultural) along particular racial lines”. Jeong is a journalist and scholar, and these arguments are happening in social media, which are always-already part of the capitalist attention economy. Jeong’s success is partly due to her confrontation of on-line harassers and responses to right-wing media figures. And her activity is the kind that rallies attention along racial lines–anti-racist, racist, etc.

Confusingly, the language she used in these tweets reads as hateful. “Dumbass fucking white people marking up the internet with their opinions like dogs pissing on fire hydrants” does, reasonably, sound like it expresses some racial animus. If we were to accept the definition of racism as merely the possession of ill will towards a race, which seems to be Andrew Sullivan’s definition, then we would have to say those were racist tweets.

We could invoke a defense here. Were the tweets satire? Did Jeong not actually have any ill will towards white people? One might wonder, similarly, whether 4chan anti-Semites are actually anti-Semitic or just trolling. The whole question of who is just trolling and who should be taken seriously on the Internet is such an interesting one. But it’s one I had to walk away from long ago after the heat got turned up on me one time. So it goes.

What everyone knows is at stake, though, is the contention that the ‘racial animus’ definition is not the real definition of racism, but rather that something like O&W’s definition is. By their account, (a) a racial project is only racist if it aligns with structures of racial domination, and (b) the structure of racial domination is a white supremacist one. Ergo, by this account, Jeong’s tweets are not racist, because insulting white people does not create or reproduce structures of white supremacist domination.

It’s worth pointing out that there are two different definitions of a word here and that neither one is inherently more correct of a definition. I’m hesitant to label the former definition “right” and the latter definition “left” because there’s nothing about the former definition that would make you, say, not want to abolish the cradle-to-prison system or any number of other real, institutional reforms. But the latter definition is favored by progressives, who have a fairly coherent world view. O&W’s theorizing is consistent with it. The helpful thing about this worldview is that it makes it difficult to complain about progressive rhetorical tactics without getting mired into a theoretical debate about their definitions, which makes it an excellent ideology for getting into fights on the Internet. This is largely what Andrew Sullivan was getting at in his critique.

What Jeong and the NYT seem to get, which some others don’t, is that comments that insult an entire race can be hurtful and bothersome even if they are not racist in the progressive sense of the term. It is not clear what we should call a racial project that is hurtful and bothersome to white people if we do not call it racist. A difficulty with the progressive definition of racism is that agreement on the application of the term is going to depend on agreement about what the dominate racial structures are. What we’ve learned in the past few years is that the left-wing view of what these racial structures are is not as widely shared as it was believed to be. For example, there are far more people who believe in anti-Semitic conspiracies, in which the dominant race is the Jews, active in American political life than was supposed. Given O&W’s definition of racism, if it were, factually, the case that Jews ran the world, then anti-Semitic comments would not be racist in the meaningful sense.

Which means that the progressive definition of racism, to be effective, depends on widespread agreement about white supremacist hegemony, which is a much, much more complicated thing to try to persuade somebody of than a particular person’s racial animus.

A number of people have been dismissing any negative reaction to the resurfacing of Jeong’s tweets, taking the opportunity to disparage that reaction as misguided and backwards. As far as I can tell, there is an argument that Jeong’s tweets are actually anti-racist. This article argues that casually disparaging white men is just something anti-racists do lightly to call attention to the dominant social structures and also the despicable behavior of some white men. Naturally, these comments are meant humorously, and not intended to refer to all white men (to assume it does it to distract from the structural issues at stake). They are jokes that should be celebrated, because the the progressives have already won this argument over #notallmen, also in 2014. Understood properly as progressive, anti-racist, social justice idiom, there is nothing offensive about Jeong’s tweets.

I am probably in a minority on this one, but I do not agree with this assessment, for a number of reasons.

First, the idea that you can have a private, in-group conversation on Twitter is absurd.

Second, the idea that a whole community of people casually expresses racial animus because of representative examples of wrongdoing by members of a social class can be alarming whether or not it’s Trump voters talking about Mexicans or anti-racists talking about white people. That alarm, as an emotional reaction, is a reality whether or not the dominant racial structures are being reproduced or challenged.

Third, I’m not convinced that as a racial project, tweets simply insulting white people really counts as “anti-racist” in a substantive sense. Anti-racist projects are “those that undo or resist structures of domination based on racial significations and identities.” Is saying “white men are bullshit” undoing a structure of domination? I’m pretty sure any white supremacist structures of domination have survived that attack. Does it resist white supremacist domination? The thrust of wise sociology of race is that what’s more important than the social meanings are the institutional structures that maintain racial inequality. Even if this statement has a meaning that is degrading to white people, it doesn’t seem to be doing any work of reorganizing resources around (anti-)racial lines. It’s just a crass insult. It may well have actually backfired, or had an effect on the racial organization of attention that neither harmed nor supported white supremacy, but rather just made its manifestation on the Internet more toxic (in response to other, much greater, toxicity, of course).

I suppose what I’m arguing for is greater recognition of nuance than either the “left” or “right” position has offered on this case. I’m saying that it is possible to engage in a racial project that is neither racist nor anti-racist. You could have a racial project that is amusingly absurd, or toxic, or cleverly insightful. Moreover, there is a complex of ethical responsibilities and principles that intersects with racial projects but is not contained by the logic of race. There are greater standards of decency that can be invoked. These are not simply constraints on etiquette. They also are relevant to the contest of racial projects and their outcomes.

Addendum, Mar. 1, 2019: I recently learned a (for me) surprising statistic via Chetty et al.‘s “Race and Economic Opportunity in the United States: An Intergenerational Perspective” (2018) work: that the median income of Asian-American households was about $17k higher than the median income of White households in 2016. I’m honestly not sure whether this matters to the preceding analysis or not. But it might, and I think it’s an interesting question whether or not it does. I add it with no further comment.

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June 24, 2018

deep thoughts about Melania Trump’s jacket: it’s masterstroke trolling

I got into an actual argument with a real person about Melania Trump’s “I really don’t care. Do U?” jacket. I’m going to double down on it and write about it because I have the hot take nobody has been talking about.

I asked this person what they thought about Melania’s jacket, and the response was, “I don’t care what she wears. She wore a jacket to a plane; so what? Is she even worth paying attention to? She’s not an important person whose opinions matter. The media is too focused on something that doesn’t matter. Just leave her alone.”

To which I responded, “So, you agree with the message on the jacket. If Melania had said that out loud, you’d say, ‘yeah, I don’t care either.’ Isn’t that interesting?”

No, it wasn’t (to the person I spoke with). It was just annoying to be talking about it in the first place. Not interesting, nothing to see here.

Back it up and let’s make some assumptions:

FLOTUS thought at least as hard about what to wear that day than I do in the morning, and is a lot better at it than I am, because she is an experience professional at appearing.
Getting the mass media to fall over itself on a gossip item about the ideological implications of first lady fashion gets you a lot of clicks, followers, attention, etc. and that is the political currency of the time. It’s the attention economy, stupid.

FLOTUS got a lot of attention for wearing that jacket because of its ambiguity. The first-order ambiguity of whether it was a coded message playing into any preexisting political perspective was going to get attention, obviously. But the second-order ambiguity, the one that makes it actually clever, is its potential reference to the attention to the first order ambiguity. The jacket, in this second order frames, literally expresses apathy about any attention given to it and questions whether you care yourself. That’s a clever, cool concept for a jacket worn on, like, the street. As a viral social media play, it is even more clever.

It’s clever because with that second-order self-referentiality, everybody who hears about it (which might be everybody in the world, who knows) has to form an opinion about it, and the most sensible opinion about it, the one which you must ultimately concluded in order to preserve your sanity, is the original one expressed: “I don’t really care.” Clever.

What’s the point? First, I’m arguing that this is was deliberate self-referential virality of the same kind I used to give Weird Twitter a name. Having researched this subject before, I claim expertise and knowing-what-I’m-talking-about. This is a tactic one can use in social media to do something clever. Annoying, but clever.

Second, and maybe more profound: in the messed up social epistemology of our time, where any image or message fractally reverberates between thousands of echo chambers, there is hardly any ground for “social facts”, or matters of consensus about the social world. Such facts require not just accurate propositional content but also enough broad social awareness of them to be believed by a quorum of the broader population. The disintegration of social facts is, probably, very challenging for American self-conception as a democracy is part of our political crisis right now.

There aren’t a lot of ways to accomplish social facts today. But one way is to send an ambiguous or controversial message that sparks a viral media reaction whose inevitable self-examinations resolve onto the substance of the original message. The social fact becomes established as a fait accompli through everybody’s conversation about it before anybody knows what’s happened.

That’s what’s happened with this jacket: it spoke the truth. We can give FLOTUS credit for that. And truth is: do any of us really care about any of this? That’s maybe not an irrelevant question, however you answer it.

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May 26, 2018

population traits, culture traits, and racial projects: a methods challenge #ica18

In a recent paper I’ve been working on with Mark Hannah that he’s presenting this week at the International Communications Association conference, we take on the question of whether and how “big data” can be used to study the culture of a population.

By “big data” we meant, roughly large social media data sets. The pitfalls of using this sort of data for any general study of a population are perhaps best articled by Tufekci (2014). In short: studies based on social media data are often sampling on the dependent variable because they only consider the people representing themselves on social media, though this is only a small portion of the population. To put it another way, the sample suffers from the 1% rule of Internet cultures: for any on-line community, only 1% create content, 10% interact with the content somehow, and the rest lurk. The behavior and attitudes of the lurkers, in addition to any field effects in the “background” of the data (latent variables in the social field of production), are all out of band and so opaque to the analyst.

By “the culture of a population”, we meant something specific: the distribution of values, beliefs, dispositions, and tastes of a particular group of people. The best source we found on this was Marsden and Swingle (1994), and article from a time before the Internet had started to transform academia. Then and perhaps now, the best way to study the distribution of culture across a broad population was a survey. The idea is that you sample the population according to some responsible statistics, you ask them some questions about their values, beliefs, dispositions, and tastes, and you report the results. Viola!

(Given the methodological divergence here, the fact that many people, especially ‘people on the Internet’, now view culture mainly through the lens of other people on the Internet is obviously a huge problem. Most people are not in this sample, and yet we pretend that it is representative because it’s easily available for analysis. Hence, our concept of culture (or cultures) is screwy, reflecting much more than is warranted whatever sorts of cultures are flourishing in a pseudonymous, bot-ridden, commercial attention economy.)

Can we productively combine social media data with surveys methods to get a better method for studying the culture of a population? We think so. We propose the following as a general method framework:

(1) Figure out the population of interest by their stable, independent ‘population traits’ and look for their activity on social media. Sample from this.

(2) Do exploratory data analysis to inductively get content themes and observations about social structure from this data.

(3) Use the inductively generated themes from step (2) to design a survey addressing cultural traits of the population (beliefs, values, dispositions, tastes).

(4) Conduct a stratified sample specifically across social media creators, synthesizers (e.g. people who like, retweet, and respond), and the general population and/or known audience, and distribute the survey.

(5) Extrapolate the results to general conclusions.

(6) Validate the conclusions with other data or not discrepancies for future iterations.

I feel pretty good about this framework as a step forward, except that in the interest of time we had to sidestep what is maybe the most interesting question raised by it, which is: what’s the difference between a population trait and a cultural trait.

Here’s what we were thinking:

Population trait	Cultural trait
Location	Twitter use (creator, synthesizer, lurker, none)
Age	Political views: left, right, center
Permanent unique identifier	Attitude towards media
	Preferred news source
	Pepsi or coke?

One thing to note: we decided that traits about media production and consumption were a subtype of cultural traits. I.e., if you use Twitter, that’s a particular cultural trait that may be correlated with other cultural traits. That makes the problem of sampling on the dependent variable explicit.

But the other thing to note is that there are certain categories that we did not put on this list. Which ones? Gender, race, etc. Why not? Because choosing whether these are population traits or cultural traits opens a big bag of worms that is the subject of active political contest. That discussion was well beyond the scope of the paper!

The dicey thing about this kind of research is that we explicitly designed it to try to avoid investigator bias. That includes the bias of seeing the world through social categories that we might otherwise naturalize of reify. Naturally, though, if we were to actually conduct this method on a sample, such as, I dunno, a sample of Twitter-using academics, we would very quickly discover that certain social categories (men, women, person of color, etc.) were themes people talked about and so would be included as survey items under cultural traits.

That is not terrible. It’s probably safer to do that than to treat them like immutable, independent properties of a person. It does seem to leave something out though. For example, say one were to identify race as a cultural trait and then ask people to identify with a race. Then one takes the results, does a factor analysis, and discovers a factor that combines a racial affinity with media preferences and participation rates. It then identifies the prevalence of this factor in a certain region with a certain age demographic. One might object to this result as a representation of a racial category as entailing certain cultural categories, and leaving out the cultural minority within a racial demographic that wants more representation.

This is upsetting to some people when, for example, Facebook does this and allows advertisers to target things based on “ethnic affinity”. Presumably, Facebook is doing just this kind of factor analysis when they identify these categories.

Arguably, that’s not what this sort of science is for. But the fact that the objection seems pertinent is an informative intuition in its own right.

Maybe the right framework for understanding why this is problematic is Omi and Winant’s racial formation theory (2014). I’m just getting into this theory recently, at the recommendation of Bruce Haynes, who I look up to as an authority on race in America. According to racial projects theory, racial categories are stable because they include both representations of groups of people as having certain qualities and social structures controlling the distribution of resources. So, the white/black divide in the U.S. is both racial stereotypes and segregating urban policy, because the divide is stable because of how the material and cultural factors reinforce each other.

This view is enlightening because it helps explain why hereditary phenotype, representations of people based on hereditary phenotype, requests for people to identify with a race even when this may not make any sense, policies about inheritance and schooling, etc. all are part of the same complex. When we were setting out to develop the method described above, we were trying to correct for a sampling bias in media while testing for the distribution of culture across some objectively determinable population variables. But the objective qualities (such as zip code) are themselves functions of the cultural traits when considered over the course of time. In short, our model, which just tabulates individual differences without looking at temporal mechanisms, is naive.

But it’s a start, if only to an interesting discussion.

References

Marsden, Peter V., and Joseph F. Swingle. “Conceptualizing and measuring culture in surveys: Values, strategies, and symbols.” Poetics 22.4 (1994): 269-289.

Omi, Michael, and Howard Winant. Racial formation in the United States. Routledge, 2014.

Tufekci, Zeynep. “Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls.” ICWSM 14 (2014): 505-514.

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December 7, 2016

post-election updates

Like a lot of people, I was completely surprised by the results of the 2016 election.

Rationally, one has to take these surprises as an opportunity to update ones point of view. As it’s been almost a month, there’s been lots of opportunity to process what’s going on.

For my own sake, more than for any reader, I’d like to note my updates here.

The first point has been best articulated by Jon Stewart:

Stewart rejected the idea that better news coverage would have changed the outcome of the election. “The idea that if [the media] had done a better job this country would have made another choice is fake,” he said. He cited Brexit as an example of an unfortunate outcome that occurred despite its lead-up being appropriately covered by outlets like the BBC, which offered a much more balanced view than CNN, for example. “Trump didn’t happen because CNN sucks—CNN just sucks,” he said.

Satire and comedy also couldn’t have stood in the way of Trump winning, Stewart said. If this election has taught us anything, he said, its that “controlling the culture does not equate to holding the power.”

I once cared a lot about “money in politics” at the level of campaign donations. After a little critical thinking, this leads naturally to a concern about the role of the media more generally in elections. Centralized media in particular will never put themselves behind a serious bid for campaign finance reform because those media institutions cash out every election. This is what it means for a problem to be “systemic”: it is caused by a tightly reinforcing feedback loop that makes it into a kind of social structural knot.

But with the 2016 presidential election, we’ve learned that Because of the Internet, media are so fragmented that even controlled media are not in control. People will read what they want to read, one way or another. Whatever narrative suits a person best, they will be able to find it on the Internet.

A perhaps unhelpful way to say this is that the Internet has set the Bourdieusian habitus free from media control.

But if the media doesn’t determine habitus, what does?

While there is a lot of consternation about the failure of polling (which is interesting), and while that could have negatively impacted Democratic campaign strategy (didn’t it?), the more insightful sounding commentary has recognized that the demographic fundamentals were in favor of Trump all along because of what he stood for economically and socially. Michael Moore predicted the election result; logically, because he was right, we should update towards his perspective; he makes essentially this point about Midwestern voters, angry men, depressed progressives, and the appeal of oddball voting all working against Hilary. But none of these conditions have as much to do with media as they do to the preexisting population conditions.

There’s a tremendous bias among those who “study the Internet” to assign tremendous political importance to the things we have expertise on: the media, algorithms, etc. My biggest update this election was that I now think that these are eclipsed in political relevance compared to macro-economic issues like globalization. At best changes to, say, the design of social media platforms are going to change things for a few people at the margins. But larger structural forces are both more effective and more consequential in politics. I bet that a prediction of the 2016 election based primarily on the demographic distribution of winners and losers according to each candidate’s energy policy, for example, would have been more valuable than all the rest of the polling and punditry combined. I suppose I was leaning this way throughout 2016, but the election sealed the deal for me.

This is a relief for me because it has revealed to me just how much of my internalization and anxieties about politics have been irrelevant. There is something very freeing in discovering that many things that you once thought were the most important issues in the world really just aren’t. If all those anxieties were proven to just be in my head, then it’s easier to let them go. Now I can start wondering about what really matters.

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August 22, 2016

becoming a #seriousacademic

I’ve decided to make a small change to my on-line identity.

For some time now, my Twitter account has been listed under a pseudonym, “Gnaeus Rafinesque”, and has had a picture of a cat. Today I’m changing it to my full name (“Sebastian Benthall”) and a picture of my face.

I chose to use a pseudonym on Twitter for a number of reasons. One reason was that I was interested in participant observation in an Internet subculture, Weird Twitter, that generally didn’t use real names because most of their activity on Twitter was very silly.

But another reason was because I was afraid of being taken seriously myself. As a student, even a graduate student, I felt it was my job to experiment, fail, be silly, and test the limits of the media I was working (and playing) within. I learned a lot from this process.

Because I often would not intend to be taken seriously on Twitter, I was reluctant to have my tweets associated with my real name. I deliberately did not try to sever all ties between my Twitter account and my “real” identity, which is reflected elsewhere on the Internet (LinkedIn, GitHub, etc.) because…well, it would have been a lot of futile work. But I think using a pseudonym and a cat picture succeeded in signalling that I wasn’t putting the full weight of my identity, with the accountability entailed by that, into my tweets.

I’m now entering a different phase of my career. Probably the most significant marker of that phase change is that I am now working as a cybersecurity professional in addition to being a graduate student. I’m back in the working world and so in a sense back to reality.

Another marker is that I’ve realized that I’ve got serious things worth saying and paying attention to, and that projecting an inconsequential, silly attitude on Twitter was undermining my ability to say those things.

It’s a little scary shifting to my real name and face on Twitter. I’m likely to censor myself much more now. Perhaps that’s as it should be.

I wonder what other platforms are out there in which I could be more ridiculous.

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March 16, 2015

correcting an error in my analysis

There is an error in my last post where I was thinking through the interpretation of 25,000,000 hit number reported for the Buzzfeed blue/black/white/whatever dress post. In that post I assumed that the distribution of viewers would be the standard one you see in on-line participation: a power law distribution with a long tail. Depending on which way you hold the diagram, the “tail” is either the enormous number of instances that only occur once (in this case, a visitor who goes to the page once and never again) or it’s population of instances that have bizarrely high occurrences (like that one guy who hit refresh on the page 100 times, and the woman that looked at the page 300 times, and…). You can turn one tail into the other by turning the histogram sideways and shaking really hard.

The problem with this analysis is that it ignores the data I’ve been getting from a significant subset of people who I’ve talked to about this in passing, which is that because the page contains some sort of well-crafted optical illusion, lots of people have looked at it once (and seen it as, say, a blue and black dress) and then looked at it again, seeing it as white and gold. In fact the article seems designed to get the reader to do just this.

If I’m being somewhat abstract in my analysis, it’s because I’ve refused to go click on the link myself. I have read too much Adorno. I hear the drumbeat of fascism in all popular culture. I do not want to take part in intelligently designed collective effervescence if I can help it. This is my idiosyncrasy.

But this inferred stickiness of the dress image has consequences for the traffic analysis. I’m sure that whoever is actually looking at the metrics on the article is tracking repeat version unique visitors. I wonder how deliberately the image was created with the idea of maximizing repeat visitations in mind, and the observed correlation between repeat and unique visitors. Repeated visits suggests sustained interest over time, whereas “mere” virality is a momentary spread of information over space. If you see content as a kind of property and sustained traffic over time as the value of that property, it makes sense to try to create things with staying power. Memetic globules forever gunking the crisscrossed manifold of attention. Culture.

Does this require a different statistical distribution to process properly? Is Cosma Shalizi right after all, and are these “power law” distributions just overhyped log-normal distributions? What happens when the generative process has a stickiness term? Is that just reflected in the power law distribution’s exponent? One day I will get a grip on this. Maybe I can do it working with mailing list data.

I’m writing this because over the weekend I was talking with a linguist and a philosopher about collective attention, a subject of great interest to me. It was the linguist who reported having looked at the dress twice and seeing it in different colors. The philosopher had not seen it. The latter’s research specialty was philosophy of mind, a kind of philosophy I care about a lot. I asked him whether in cases of collective attention the mental representation supervenes reductively on many individual minds or on more than that. He said that this is a matter of current debate but that he wants to argue that collective attention means more than my awareness of X, and my awareness of your awareness of X, ad infinitum. Ultimately I’m a mathematical person and am happy to see the limit of the infinite process as itself and its relationship with what it reduces to mediated by the logic of infinitesimals. But perhaps even this is not enough. I gave the philosopher my recommendation of Soren Brier and Ulanowicz, who together I think provide the groundwork needed for an ontology of macroorganic mentality and representation. The operationalization of these theories is the goal of my work at Glass Bead Labs.

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March 7, 2015

25,000,000 re: @ftrain

It was gratifying to read Paul Ford’s reluctant think piece about the recent dress meme epidemic.

The most interesting fact in the article was that Buzzfeed’s dress article has gotten 25 million views:

People are also keenly aware that BuzzFeed garnered 25 million views (and climbing) for its article about the dress. Twenty-five million is a very, very serious number of visitors in a day — the sort of traffic that just about any global media property would kill for (while social media is like, ho hum).

I’ve recently become interested in the question: how important is the Internet, really? Those of us who work closely with it every day see it as central to our lives. Logically, we would tend to extrapolate and think that it is central to everybody’s life. If we are used to sampling from other’s experience using social media, we would see that social media is very important in everybody’s life, confirming this suspicion.

This is obviously a kind of sampling bias though.

This is where the 25,000,000 figure comes in handy. My experience of the dress meme was that it was completely ubiquitous. Literally nobody I was following on Twitter who was tweeting that day was not at least referencing the dress. The meme also got to me via an email backchannel, and came up in a seminar. Perhaps you had a similar experience: you and everyone you knew was aware of this meme.

Let’s assume that 25 million is an indicator of the order of magnitude of people that learned about this meme. If you googled the dress question, you probably clicked the article. Maybe you clicked it twice. Maybe you clicked it twenty times and you are an outlier. Maybe you didn’t click it at all. It’s plausible that it evens out and the actual number of people who were aware of the meme is somewhere between 10 million and 50 million.

That’s a lot of people. But–and this is really my point–it’s not that many people, compared to everybody. There’s about 300 million people in the United States. There’s over 7 billion people on the planet. Who are the tenth of the population who were interested in the dress? If you are reading this blog, they are probably people a lot like you or I. Who are the other ~93% of people in the U.S.?

I’ve got a bold hypothesis. My hypothesis is that the other 90% of people are people who have lives. I mean this in the sense of the idiom “get a life“, which has fallen out of fashion for some reason. Increasingly, I’m becoming interested in the vast but culturally foreign population of people who followed this advice at some point in their lives and did not turn back. Does anybody know of any good ethnographic work about them? Where do they hang out in the Bay Area?

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November 29, 2014

analysis of content vs. analysis of distribution of media

A theme that keeps coming up for me in work and conversation lately is the difference between analysis of the content of media and analysis of the distribution of media.

Analysis of content looks for the tropes, motifs, psychological intentions, unconscious historical influences, etc. of the media. Over Thanksgiving a friend of mine was arguing that the Scorpions were a dog whistle to white listeners because that band made a deliberate move to distance themselves from influence of black music on rock. Contrast this with Def Leppard. He reached this conclusion based by listening carefully to the beats and contextualizing them in historical conversations that were happening at the time.

Analysis of distribution looks at information flow and the systemic channels that shape it. How did the telegraph change patterns of communication? How did television? Radio? The Internet? Google? Facebook? Twitter? Ello? Who is paying for the distribution of this media? How far does the signal reach?

Each of these views is incomplete. Just as data underdetermines hypotheses, media underdetermines its interpretation. In both cases, a more complete understanding of the etiology of the data/media is needed to select between competing hypotheses. We can’t truly understand content unless we understand the channels through which it passes.

Analysis of distribution is more difficult than analysis of content because distribution is less visible. It is much easier to possess and study data/media than it is to possess and study the means of distribution. The means of distribution are a kind of capital. Those that study it from the outside must work hard to get anything better than a superficial view of it. Those on the inside work hard to get a deep view of it that stays up to date.

Part of the difficulty of analysis of distribution is that the system of distribution depends on the totality of information passing through it. Communication involves the dynamic engagement of both speakers and an audience. So a complete analysis of distribution must include an analysis of content for every piece of implicated content.

One thing that makes the content analysis necessary for analysis of distribution more difficult than what passes for content analysis simpliciter is that the former needs to take into account incorrect interpretation. Suppose you were trying to understand the popularity of Fascist propaganda in pre-WWII Germany and were interested in how the state owned the mass media channels. You could initially base your theory simply on how people were getting bombarded by the same information all the time. But you would at some point need to consider how the audience was reacting. Was it stirring feelings of patriotic national identity? Did they experience communal feelings with others sharing similar opinions? As propaganda provided interpretations of Shakespeare saying he was secretly a German and denunciation of other works as “degenerate art”, did the audience believe this content analysis? Did their belief in the propaganda allow them to continue to endorse the systems of distribution in which they took part?

This shows how the question of how media is interpreted is a political battle fought by many. Nobody fighting these battles is an impartial scientist. Since one gets an understanding of the means of distribution through impartial science, and since this understanding of the means of distribution is necessary for correct content analysis, we can dismiss most content analysis as speculative garbage, from a scientific perspective. What this kind of content analysis is instead is art. It can be really beautiful and important art.

On the other hand, since distribution analysis depends on the analysis of every piece of implicated content, distribution analysis is ultimately hopeless without automated methods for content analysis. This is one reason why machine learning techniques for analyzing text, images, and video are such a hot research area. While the techniques for optimizing supply chain logistics (for example) are rather old, the automated processing of media is a more subtle problem precisely because it involves the interpretation and reinterpretation by finite subjects.

By “finite subject” here I mean subjects that are inescapably limited by the boundaries of their own perspective. These limits are what makes their interpretation possible and also what makes their interpretation incomplete.

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November 26, 2014

things I’ve been doing while not looking at twitter

Twitter was getting me down so I went on a hiatus. I’m still on that hiatus. Instead of reading Twitter, I’ve been:

Reading Fred Turner’s The Democratic Surround. This is a great book about the relationship between media and democracy. Since a lot of my interest in Twitter has been because of my interest in the media and democracy, this gives me those kinds of jollies without the soap opera trainwreck of actually participating in social media.
Going to arts events. There was a staging of Rhinoceros at Berkeley. It’s an absurdist play in which a small French village is suddenly stricken by an epidemic wherein everybody is transformed into a rhinoceros. It’s probably an allegory for the rise of Communism or Fascism but the play is written so that it’s completely ambiguous. Mainly it’s about conformity in general, perhaps ideological conformity but just as easily about conformity to non-ideology, to a state of nature (hence, the animal form, rhinoceros.) It’s a good play.
I’ve been playing Transistor. What an incredible game! The gameplay is appealingly designed and original, but beyond that it is powerfully written an atmospheric. In many ways it can be read as a commentary on the virtual realities of the Internet and the problems with them. Somehow there was more media attention to GamerGate than to this one actually great game. Too bad.
I’ve been working on papers, software, and research in anticipation of the next semester. Lots of work to do!

Above all, what’s great about unplugging from social media is that it isn’t actually unplugging at all. Instead, you can plug into a smarter, better, deeper world of content where people are more complex and reasonable. It’s elevating!

I’m writing this because some time ago it was a matter of debate whether or not you can ‘just quit Facebook’ etc. It turns out you definitely can and it’s great. Go for it!

(Happy to respond to comments but won’t respond to tweets until back from the hiatus)

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Category: social media

Case Study: Jeong’s tweets